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{ "count": 52, "next": "?page=2", "previous": null, "list": [ { "name": "compareMS2", "description": "compareMS2 is a tool for comparing sets of (tandem) mass spectra for clustering samples, molecular phylogenetics, identification of biological species or tissues, and quality control. compareMS2 currently consumes Mascot Generic Format, or MGF, and produces output in a variety of common image and distance matrix formats.", "homepage": "https://github.com/524D/compareMS2", "biotoolsID": "comparems2", "biotoolsCURIE": "biotools:comparems2", "version": [ "1.0", "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2424", "term": "Comparison" }, { "uri": "http://edamontology.org/operation_0567", "term": "Phylogenetic tree visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3651", "term": "MGF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3272", "term": "Species tree" }, "format": [ { "uri": "http://edamontology.org/format_3603", "term": "PNG" }, { "uri": "http://edamontology.org/format_3604", "term": "SVG" } ] }, { "data": { "uri": "http://edamontology.org/data_2855", "term": "Distance matrix" }, "format": [ { "uri": "http://edamontology.org/format_1991", "term": "mega" }, { "uri": "http://edamontology.org/format_1912", "term": "Nexus format" }, { "uri": "http://edamontology.org/format_1910", "term": "newick" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0084", "term": "Phylogeny" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C", "JavaScript" ], "license": "MIT", "collectionID": [ "ms-utils", "Proteomics" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Netherlands" ], "elixirCommunity": [ "Proteomics" ], "link": [ { "url": "https://github.com/524D/compareMS2", "type": [ "Repository" ], "note": null }, { "url": "https://www.ms-utils.org/compareMS2.html", "type": [ "Software catalogue" ], "note": null }, { "url": "https://research-software-directory.org/software/comparems2", "type": [ "Software catalogue" ], "note": null } ], "download": [ { "url": "http://www.ms-utils.org/compareMS2.c", "type": "Source code", "note": null, "version": "1.0" }, { "url": "http://www.ms-utils.org/compareMS2.html", "type": "Binaries", "note": null, "version": "1.0" }, { "url": "http://www.ms-utils.org/compareMS2.c", "type": "Source code", "note": null, "version": "1.0" }, { "url": "https://github.com/524D/compareMS2/tree/main/src", "type": "Source code", "note": null, "version": "2.0" }, { "url": "https://github.com/524D/compareMS2/tree/main", "type": "Binaries", "note": null, "version": "2.0" } ], "documentation": [ { "url": "http://www.ms-utils.org/compareMS2.html", "type": [ "General", "Command-line options" ], "note": null }, { "url": "https://github.com/524D/compareMS2", "type": [ "General", "User manual", "Command-line options", "Installation instructions" ], "note": null } ], "publication": [ { "doi": "10.1002/rcm.6162", "pmid": "22368051", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Molecular phylogenetics by direct comparison of tandem mass spectra", "abstract": "Rationale: Molecular phylogenetics is the study of evolution and relatedness of organisms or genes. Mass spectrometry is used routinely for bacterial identification and has also been used for phylogenetic analysis, for instance from bone material. Unfortunately, only a small fraction of the acquired tandem mass spectra allow direct interpretation. Methods: We describe a new algorithm and software for molecular phylogenetics using pairwise comparisons of tandem mass spectra from enzymatically digested proteins. The spectra need not be annotated and all acquired data is used in the analysis. To demonstrate the method, we analyzed tryptic digests of sera from four great apes and two other primates. Results: The distribution of spectra dot products for thousands of tandem mass spectra collected from two samples provides a measure on the fraction of shared peptides between the two samples. When inverted, this becomes a distance metric. By pairwise comparison between species and averaging over four individuals per species, it was possible to reconstruct the unique correct phylogenetic tree for the great apes and other primates. Conclusions: The new method described here has several attractive features compared with existing methods, among them simplicity, the unbiased use of all acquired data rather than a small subset of spectra, and the potential use of heavily degraded proteins or proteins with a priori unknown modifications. © 2012 John Wiley & Sons, Ltd.", "date": "2012-04-15T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Palmblad M." }, { "name": "Deelder A.M." } ], "journal": "Rapid Communications in Mass Spectrometry" } }, { "doi": "10.1021/acs.jproteome.2c00457", "pmid": "36173614", "pmcid": "PMC9903320", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry Datasets", "abstract": "It has long been known that biological species can be identified from mass spectrometry data alone. Ten years ago, we described a method and software tool, compareMS2, for calculating a distance between sets of tandem mass spectra, as routinely collected in proteomics. This method has seen use in species identification and mixture characterization in food and feed products, as well as other applications. Here, we present the first major update of this software, including a new metric, a graphical user interface and additional functionality. The data have been deposited to ProteomeXchange with dataset identifier PXD034932.", "date": "2023-02-03T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Marissen R." }, { "name": "Varunjikar M.S." }, { "name": "Laros J.F.J." }, { "name": "Rasinger J.D." }, { "name": "Neely B.A." }, { "name": "Palmblad M." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1021/acs.jproteome.1c00528", "pmid": "34523928", "pmcid": "PMC8491155", "type": [ "Review" ], "version": "2.0", "note": null, "metadata": { "title": "Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics Experiments in the Light of Proteomics", "abstract": "Science is full of overlooked and undervalued research waiting to be rediscovered. Proteomics is no exception. In this perspective, we follow the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing tryptic peptides across animal species. This pioneering work directly led to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics. In the decades following, proteins continued to provide essential clues on evolutionary history. While technology has continued to improve, contemporary proteomics has strayed from this larger biological context, rarely comparing species or asking how protein structure, function, and interactions have evolved. Here we recombine proteomics with molecular phylogenetics, highlighting the value of framing proteomic results in a larger biological context and how almost forgotten research, though technologically surpassed, can still generate new ideas and illuminate our work from a different perspective. Though it is infeasible to read all research published on a large topic, looking up older papers can be surprisingly rewarding when rediscovering a \"gem\"at the end of a long citation chain, aided by digital collections and perpetually helpful librarians. Proper literature study reduces unnecessary repetition and allows research to be more insightful and impactful by truly standing on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/) as dataset MSV000087993.", "date": "2021-10-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Neely B.A." }, { "name": "Palmblad M." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "lumc.nl", "email": null, "url": "https://www.lumc.nl", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Support" ], "note": null }, { "name": "Magnus Palmblad", "email": "magnus.palmblad@gmail.com", "url": "https://github.com/magnuspalmblad", "orcidid": "http://orcid.org/0000-0002-5865-8994", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact", "Documentor" ], "note": null }, { "name": "Rob Marissen", "email": null, "url": "https://github.com/524D", "orcidid": "https://orcid.org/0000-0002-1220-9173", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2016-04-15T11:52:42Z", "lastUpdate": "2025-04-16T14:22:04.957317Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "ARTEMIS", "description": "a method for topology-independent superposition of RNA 3D structures and structure-based sequence alignment", "homepage": "https://github.com/david-bogdan-r/ARTEMIS", "biotoolsID": "artemis3D", "biotoolsCURIE": "biotools:artemis3D", "version": [ "version 1.51" ], "otherID": [], "relation": [ { "biotoolsID": "artem", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0503", "term": "Pairwise structure alignment" }, { "uri": "http://edamontology.org/operation_2518", "term": "Nucleic acid structure comparison" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1459", "term": "Nucleic 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"http://edamontology.org/format_1476", "term": "PDB" } ] } ], "note": null, "cmd": "python3 artemis.py r=FILENAME q=FILENAME [OPTIONS]" } ], "toolType": [ "Command-line tool", "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_0077", "term": "Nucleic acids" }, { "uri": "http://edamontology.org/topic_0097", "term": "Nucleic acid structure analysis" }, { "uri": "http://edamontology.org/topic_0102", "term": "Mapping" }, { "uri": "http://edamontology.org/topic_3511", "term": "Nucleic acid sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0654", "term": "DNA" }, { "uri": "http://edamontology.org/topic_0099", "term": "RNA" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [ "3D-BioInfo-Structure-Function" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/david-bogdan-r/ARTEMIS", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/david-bogdan-r/ARTEMIS", "type": "Source code", "note": null, "version": "version 1.5" } ], "documentation": [ { "url": "https://github.com/david-bogdan-r/ARTEMIS/blob/main/README.md", "type": [ "Quick start guide" ], "note": "README file" }, { "url": "https://github.com/david-bogdan-r/ARTEMIS/blob/main/ARTEMIS_TUTORIAL_v1.51.pdf", "type": [ "User manual" ], "note": "Tutorial in pdf" } ], "publication": [ { "doi": "10.1093/nar/gkae758", "pmid": "39258540", "pmcid": "PMC11472068", "type": [ "Primary" ], "version": "version 1.5", "note": null, "metadata": { "title": "ARTEMIS: a method for topology-independent superposition of RNA 3D structures and structure-based sequence alignment", "abstract": "Non-coding RNAs play a major role in diverse processes in living cells with their sequence and spatial structure serving as the principal determinants of their function. Superposition of RNA 3D structures is the most accurate method for comparative analysis of RNA molecules and for inferring structure-based sequence alignments. Topology-independent superposition is particularly relevant, as evidenced by structurally similar RNAs with sequence permutations such as tRNA and Y RNA. To date, state-of-the-art methods for RNA 3D structure superposition rely on intricate heuristics, and the potential for topology-independent superposition has not been exhausted. Recently, we introduced the ARTEM method for unrestrained pairwise superposition of RNA 3D modules and now we developed it further to solve the global RNA 3D structure alignment problem. Our new tool ARTEMIS significantly outperforms state-of-the-art tools in both sequentially-ordered and topology-independent RNA 3D structure superposition. Using ARTEMIS we discovered a helical packing motif to be preserved within different backbone topology contexts across various non-coding RNAs, including multiple ribozymes and riboswitches. We anticipate that ARTEMIS will be essential for elucidating the landscape of RNA 3D folds and motifs featuring sequence permutations that thus far remained unexplored due to limitations in previous computational approaches.", "date": "2024-10-14T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Bohdan D.R." }, { "name": "Bujnicki J.M." }, { "name": "Baulin E.F." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1101/2024.04.06.588371", "pmid": null, "pmcid": null, "type": [], "version": "version 1.0", "note": null, "metadata": null } ], "credit": [ { "name": "Davyd Bohdan", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-6456-6658", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Janusz Bujnicki", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-6633-165X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Eugene Baulin", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-4694-9783", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "febos", "additionDate": "2024-09-09T07:49:35.385723Z", "lastUpdate": "2025-01-30T09:07:50.841042Z", "editPermission": { "type": "private", "authors": [ "febos" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ChannelsDB 2.0", "description": "A comprehensive resource of channels, pores and tunnels found in biomacromolecular structures deposited in the Protein Data Bank.", "homepage": "https://channelsdb2.biodata.ceitec.cz/", "biotoolsID": "channelsdb", "biotoolsCURIE": "biotools:channelsdb", "version": [ "2.0" ], "otherID": [], "relation": [ { "biotoolsID": "mole", "type": "uses" }, { "biotoolsID": "caver", "type": "uses" }, { "biotoolsID": "moleonline_2.0", "type": "uses" }, { "biotoolsID": "caver_web", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Data deposition" }, { "uri": "http://edamontology.org/operation_0570", "term": "Structure visualisation" }, { "uri": "http://edamontology.org/operation_0250", "term": "Protein property calculation" }, { "uri": "http://edamontology.org/operation_0245", "term": "Protein structural motif recognition" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3021", "term": "UniProt accession" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_1127", "term": "PDB ID" }, "format": [ { "uri": "http://edamontology.org/format_1477", "term": "mmCIF" }, { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_3464", "term": "JSON" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_2878", "term": "Protein structural motif" }, "format": [ { "uri": "http://edamontology.org/format_2332", "term": "XML" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_1317", "term": "Structural biology" }, { "uri": "http://edamontology.org/topic_3306", "term": "Biophysics" }, { "uri": "http://edamontology.org/topic_0123", "term": "Protein properties" }, { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_0821", "term": "Enzymes" }, { "uri": "http://edamontology.org/topic_0820", "term": "Membrane and lipoproteins" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_3068", "term": "Literature and language" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript", "C#" ], "license": "Freeware", "collectionID": [ "LCC NCBR", "ELIXIR-CZ" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [ { "url": "https://channelsdb2.biodata.ceitec.cz", "type": [ "Service" ], "note": null } ], "download": [], "documentation": [ { "url": "https://channelsdb2.biodata.ceitec.cz/documentation.html", "type": [ "User manual", "Quick start guide" ], "note": "Database content\nChannels nomenclature\nMOLE settings\nList of cofactors used for channel determination.\nDescription how to read the resuls page.\nHow to access content of the database programatically." }, { "url": "https://channelsdb2.biodata.ceitec.cz/methods.html", "type": [ "General", "FAQ" ], "note": "Info about methodology" }, { "url": "https://channelsdb2.biodata.ceitec.cz/about.html", "type": [ "Citation instructions", "Contributions policy" ], "note": null }, { "url": "https://channelsdb2.biodata.ceitec.cz/api", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkx868", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": "1.0", "note": null, "metadata": { "title": "ChannelsDB: Database of biomacromolecular tunnels and pores", "abstract": "ChannelsDB (http://ncbr.muni.cz/ChannelsDB) is a database providing information about the positions, geometry and physicochemical properties of channels (pores and tunnels) found within biomacromolecular structures deposited in the Protein Data Bank. Channels were deposited from two sources; from literature using manual deposition and from a software tool automatically detecting tunnels leading to the enzymatic active sites and selected cofactors, and transmembrane pores. The database stores information about geometrical features (e.g. length and radius profile along a channel) and physicochemical properties involving polarity, hydrophobicity, hydropathy, charge and mutability. The stored data are interlinked with available UniProt annotation data mapping known mutation effects to channel-lining residues. All structures with channels are displayed in a clear interactive manner, further facilitating data manipulation and interpretation. As such, ChannelsDB provides an invaluable resource for research related to deciphering the biological function of biomacromolecular channels.", "date": "2018-01-01T00:00:00Z", "citationCount": 29, "authors": [ { "name": "Pravda L." }, { "name": "Sehnal D." }, { "name": "Svobodova VaEkova R." }, { "name": "Navratilova V." }, { "name": "Tousek D." }, { "name": "Berka K." }, { "name": "Otyepka M." }, { "name": "Koca J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkad1012", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "ChannelsDB 2.0:ã comprehensive database of protein tunnelsãnd pores in Alpha Foldera", "abstract": "ChannelsDB 2.0 isãn updated database providing str uct ural informationãbout the position, geometryãnd ph y sicochemical properties of protein channels-tunnelsãnd pores-within deposited biomacromolecular str uct ures from PDBãnd AlphaFoldDB databases. T he ne wly deposited information originated from several sources. Firstly, we included data calculated usingã popular CAVER tool to complement the datã obtãined using original MOLE tool for detectionãndãnalysis of protein tunnelsãnd pores. Secondly, weãdded tunnels starting from cofactors within the AlphaFill database to enlarge the scope of the database to protein models based on Uniprot. This has enlargedã vãilable channelãnnotations ∼4.6 timesãs of 1 September 2023. The database stores informationãbout geometrical features, e.g. lengthãnd radius,ãnd ph y sico-chemical properties based on channel-liningãminoãcids. The stored dataãre interlinked with theã vãilable UniP rot mutãtionãnnotãtion datã. ChannelsDB 2.0 providesãn excellent resource for deepãnalysis of the role of biomacromolecular tunnelsãnd pores. The database isãvailable free of charge: ht tps://c hannelsdb2.biodata.ceitec.cz .", "date": "2024-01-05T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Spackova A." }, { "name": "Vavra O." }, { "name": "Racek T." }, { "name": "Bazgier V." }, { "name": "Sehnal D." }, { "name": "Damborsky J." }, { "name": "Svobodova R." }, { "name": "Bednar D." }, { "name": "Berka K." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Lukáš Pravda", "email": "xpravda@ncbr.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-6435-4719", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "David Sehnal", "email": "david.sehnal@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-0682-3089", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Karel Berka", "email": "karel.berka@upol.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-9472-2589", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Contributor" ], "note": null }, { "name": "Radka Svobodová", "email": "radka.svobodova@ceitec.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-3840-8760", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Provider" ], "note": null }, { "name": "David Bednář", "email": "222755@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-6803-0340", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Palacky University Olomouc", "email": null, "url": "https://www.upol.cz/en/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null }, { "name": "Masaryk University Brno", "email": null, "url": "https://www.muni.cz/en", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null }, { "name": "Václav Bazgier", "email": "vaclav.bazgier@upol.cz", "url": null, "orcidid": "https://orcid.org/0000-0003-3393-3010", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Documentor", "Contributor" ], "note": null }, { "name": "Anna Špačková", "email": "anna.spackova@upol.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-7142-3092", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Documentor" ], "note": null }, { "name": "Ondřej Vávra", "email": "vavra@enantis.com", "url": null, "orcidid": "https://orcid.org/0000-0003-1396-2543", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Tomáš Raček", "email": "324965@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-0296-2452", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer" ], "note": null }, { "name": "Jiří Damborský", "email": "jiri@chemi.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-7848-8216", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "ELIXIR-CZ", "additionDate": "2017-08-03T12:46:16Z", "lastUpdate": "2024-11-25T13:45:26.806319Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PROTEOFORMER", "description": "Proteogenomic pipeline integrating ribosome profiling (RIBO-seq) data in the search for new proteoforms in proteomic validation data. The pipeline does a genome-wide construction of candidate translation products based on ribosome occupancy.", "homepage": "https://github.com/Biobix/proteoformer", "biotoolsID": "proteoformer", "biotoolsCURIE": "biotools:proteoformer", "version": [ "1.0", "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2423", "term": "Prediction and recognition" }, { "uri": "http://edamontology.org/operation_3563", "term": "RNA-seq read count analysis" }, { "uri": "http://edamontology.org/operation_3225", "term": "Variant classification" }, { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" }, { "uri": "http://edamontology.org/operation_2284", "term": "Nucleic acid density plotting" }, { "uri": "http://edamontology.org/operation_3198", "term": "Read mapping" }, { "uri": "http://edamontology.org/operation_3182", "term": "Genome alignment" }, { "uri": "http://edamontology.org/operation_3800", "term": "RNA-Seq quantification" }, { "uri": "http://edamontology.org/operation_3661", "term": "SNP annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3496", "term": "RNA sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_3621", "term": "SQLite format" } ] }, { "data": { "uri": "http://edamontology.org/data_2886", "term": "Protein sequence record" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": null, "cmd": "perl mapping.pl --help" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3120", "term": "Protein variants" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "R", "Perl", "SQL", "Python" ], "license": "GPL-3.0", "collectionID": [ "BIG N2N", "Proteomics", "BioBix", "UGent" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Biobix/proteoformer", "type": [ "Repository" ], "note": "GitHub tool repo (PROTEOFORMER version 2.0)" }, { "url": "http://galaxy.ugent.be/", "type": [ "Galaxy service" ], "note": "Galaxy service of PROTEOFORMER version 1.0 (the Galaxy service of PROTEOFORMER version 2.0 is under way)" }, { "url": "http://www.biobix.be/research/downloads/proteoformer/", "type": [ "Other" ], "note": "Explanation of the tool on the lab's website" } ], "download": [ { "url": "https://github.com/Biobix/proteoformer", "type": "Source code", "note": "GitHub repo", "version": "2.0" }, { "url": "https://github.com/Biobix/proteoformer/tree/master/Galaxy%20files", "type": "Tool wrapper (Galaxy)", "note": "Galaxy wrapper files", "version": "1.0" } ], "documentation": [ { "url": "https://github.com/Biobix/proteoformer/blob/master/README.md", "type": [ "User manual" ], "note": "Full elaborate documentation on usage and installation with lots of examples. Main documentation source." }, { "url": "https://github.com/Biobix/proteoformer/blob/master/LICENSE", "type": [ "Terms of use" ], "note": "GPU 3.0 license" } ], "publication": [ { "doi": "10.1093/nar/gku1283", "pmid": "25510491", "pmcid": "PMC4357689", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "PROTEOFORMER: Deep proteome coverage through ribosome profiling and MS integration", "abstract": "An increasing amount of studies integrate mRNA sequencing data into MS-based proteomics to complement the translation product search space. However, several factors, including extensive regulation of mRNA translation and the need for threeor six-frame-translation, impede the use of mRNAseq data for the construction of a protein sequence search database.With that inmind, we developed the PROTEOFORMER tool that automatically processes data of the recently developed ribosome profiling method (sequencing of ribosome-protected mRNA fragments), resulting in genome-wide visualization of ribosome occupancy. Our tool also includes a translation initiation site calling algorithm allowing the delineation of the open reading frames (ORFs) of all translation products. A complete protein synthesisbased sequence database can thus be compiled for mass spectrometry-based identification. This approach increases the overall protein identification rates with 3% and 11% (improved and new identifications) for human and mouse, respectively, and enables proteome-wide detection of 5'-extended proteoforms, upstream ORF translation and near-cognate translation start sites. The PROTEOFORMER tool is available as a stand-alone pipeline and has been implemented in the galaxy framework for ease of use.", "date": "2015-03-11T00:00:00Z", "citationCount": 111, "authors": [ { "name": "Crappe J." }, { "name": "Ndah E." }, { "name": "Koch A." }, { "name": "Steyaert S." }, { "name": "Gawron D." }, { "name": "De Keulenaer S." }, { "name": "De Meester E." }, { "name": "De Meyer T." }, { "name": "Van Criekinge W." }, { "name": "Van Damme P." }, { "name": "Menschaert G." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1074/mcp.ra118.001218", "pmid": "31040227", "pmcid": "PMC6692777", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "PROTEOFORMER 2.0: Further developments in the ribosome profiling-assisted proteogenomic hunt for new proteoforms", "abstract": "PROTEOFORMER is a pipeline that enables the automated processing of data derived from ribosome profiling (RIBO-seq, i.e. The sequencing of ribosome-protected mRNA fragments). As such, genome-wide ribosome occupancies lead to the delineation of data-specific translation product candidates and these can improve the mass spectrometry-based identification. Since its first publication, different upgrades, new features and extensions have been added to the PROTEOFORMER pipeline. Some of the most important upgrades include P-site offset calculation during mapping, comprehensive data preexploration, the introduction of two alternative proteoform calling strategies and extended pipeline output features. These novelties are illustrated by analyzing ribosome profiling data of human HCT116 and Jurkat data. The different proteoform calling strategies are used alongside one another and in the end combined together with reference sequences from UniProt. Matching mass spectrometry data are searched against this extended search space with MaxQuant. Overall, besides annotated proteoforms, this pipeline leads to the identification and validation of different categories of new proteoforms, including translation products of up- and downstream open reading frames, 5' and 3' extended and truncated proteoforms, single amino acid variants, splice variants and translation products of so-called noncoding regions. Further, proof-of-concept is reported for the improvement of spectrum matching by including Prosit, a deep neural network strategy that adds extra fragmentation spectrum intensity features to the analysis. In the light of ribosome profiling-driven proteogenomics, it is shown that this allows validating the spectrum matches of newly identified proteoforms with elevated stringency. These updates and novel conclusions provide new insights and lessons for the ribosome profiling-based proteogenomic research field.", "date": "2019-01-01T00:00:00Z", "citationCount": 36, "authors": [ { "name": "Verbruggen S." }, { "name": "Ndah E." }, { "name": "Van Criekinge W." }, { "name": "Gessulat S." }, { "name": "Kuster B." }, { "name": "Wilhelm M." }, { "name": "Van Damme P." }, { "name": "Menschaert G." } ], "journal": "Molecular and Cellular Proteomics" } } ], "credit": [ { "name": "Steven Verbruggen", "email": "Steven.Verbruggen@UGent.be", "url": null, "orcidid": "https://orcid.org/0000-0001-9441-9539", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Documentor", "Maintainer" ], "note": "Main developer of the 2.0 version" }, { "name": "Gerben Menschaert", "email": "Gerben.Menschaert@ugent.be", "url": null, "orcidid": "https://orcid.org/0000-0002-7575-2085", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Contributor" ], "note": "PI of this project" }, { "name": "Jeroen Crappé", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-1677-9533", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "Main developer of the 1.0 version" }, { "name": "Elvis Ndah", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "Main developer of the 1.0 version" }, { "name": "Sandra Steyaert", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Contributor to the 1.0 version" }, { "name": "Alexander Koch", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Contributor to the 1.0 version" }, { "name": "Ghent University", "email": null, "url": "https://www.ugent.be/en", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null }, { "name": "BioBix", "email": null, "url": "http://www.biobix.be/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [], "note": null } ], "owner": "Katrijn.Vannerum@ugent.be", "additionDate": "2016-05-17T10:17:55Z", "lastUpdate": "2024-11-24T21:08:45.743010Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "StevenVerbruggen" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "EBprot", "description": "Perseus plugin for differential protein abundance analysis of labeling-based and label-free quantitative proteomics data", "homepage": "https://github.com/cssblab/EBprot", "biotoolsID": "ebprot", "biotoolsCURIE": "biotools:ebprot", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3634", "term": "Label-free quantification" }, { "uri": "http://edamontology.org/operation_3635", "term": "Labeled quantification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0945", "term": "Peptide identification" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Plug-in" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Windows" ], "language": [ "C++" ], "license": "Apache-2.0", "collectionID": [ "Proteomics" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/cssblab/EBprot", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/cssblab/EBprot/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/cssblab/EBprot/releases", "type": "Software package", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/cssblab/EBprot/wiki", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jproteome.8b00483", "pmid": "30411623", "pmcid": "PMC6433620", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "EBprotV2: A Perseus Plugin for Differential Protein Abundance Analysis of Labeling-Based Quantitative Proteomics Data", "abstract": "We present EBprotV2, a Perseus plugin for peptide-ratio-based differential protein abundance analysis in labeling-based proteomics experiments. The original version of EBprot models the distribution of log-transformed peptide-level ratios as a Gaussian mixture of differentially abundant proteins and nondifferentially abundant proteins and computes the probability score of differential abundance for each protein based on the reproducible magnitude of peptide ratios. However, the fully parametric model can be inflexible, and its R implementation is time-consuming for data sets containing a large number of peptides (e.g., >100000). The new tool built in the C++ language is not only faster in computation time but also equipped with a flexible semiparametric model that handles skewed ratio distributions better. We have also developed a Perseus plugin for EBprotV2 for easy access to the tool. In addition, the tool now offers a new submodule (MakeGrpData) to transform label-free peptide intensity data into peptide ratio data for group comparisons and performs differential abundance analysis using mixture modeling. This approach is especially useful when the label-free data have many missing peptide intensity data points.", "date": "2019-02-01T00:00:00Z", "citationCount": 3, "authors": [ { "name": "Koh H.W.L." }, { "name": "Zhang Y." }, { "name": "Vogel C." }, { "name": "Choi H." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1002/pmic.201400620", "pmid": "25913743", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "EBprot: Statistical analysis of labeling-based quantitative proteomics data", "abstract": "Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/).", "date": "2015-08-01T00:00:00Z", "citationCount": 10, "authors": [ { "name": "Koh H.W.L." }, { "name": "Swa H.L.F." }, { "name": "Fermin D." }, { "name": "Ler S.G." }, { "name": "Gunaratne J." }, { "name": "Choi H." } ], "journal": "Proteomics" } } ], "credit": [ { "name": "Hiromi W.L. Koh", "email": "hiromi_koh@nuhs.edu.sg", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Yunbin Zhang", "email": "yz2236@nyu.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Christine Vogel", "email": "cvogel@nyu.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Hyungwon Choi", "email": "hwchoi@nus.edu.sg", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2019-01-23T12:32:59Z", "lastUpdate": "2024-11-24T21:05:25.086214Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "InterEvDock", "description": "Ab initio protein docking based on rigid-body sampling followed by consensus scoring using physics-based and statistical potentials, including the InterEvScore function specifically developed to incorporate co-evolutionary information in docking.", "homepage": "https://mobyle.rpbs.univ-paris-diderot.fr/cgi-bin/portal.py#forms::InterEvDock2", "biotoolsID": "interevdock2", "biotoolsCURIE": "biotools:interevdock2", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3899", "term": "Protein-protein docking" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2877", "term": "Protein complex" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0477", "term": "Protein modelling" }, { "uri": "http://edamontology.org/operation_3899", "term": "Protein-protein docking" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2877", "term": "Protein complex" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_2275", "term": "Molecular modelling" }, { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [], "language": [], "license": "Freeware", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock2/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gky377", "pmid": "29741647", "pmcid": "PMC6030979", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "InterEvDock2: An expanded server for protein docking using evolutionary and biological information from homology models and multimeric inputs", "abstract": "Computational protein docking is a powerful strategy to predict structures of protein-protein interactions and provides crucial insights for the functional characterization of macromolecular cross-talks. We previously developed InterEvDock, a server for ab initio protein docking based on rigid-body sampling followed by consensus scoring using physics-based and statistical potentials, including the InterEvScore function specifically developed to incorporate co-evolutionary information in docking. InterEvDock2 is a major evolution of InterEvDock which allows users to submit input sequences - not only structures - and multimeric inputs and to specify constraints for the pairwise docking process based on previous knowledge about the interaction. For this purpose, we added modules in InterEvDock2 for automatic template search and comparative modeling of the input proteins. The InterEvDock2 pipeline was benchmarked on 812 complexes for which unbound homology models of the two partners and co-evolutionary information are available in the PPI4DOCK database. InterEvDock2 identified a correct model among the top 10 consensus in 29% of these cases (compared to 15-24% for individual scoring functions) and at least one correct interface residue among 10 predicted in 91% of these cases. InterEvDock2 is thus a unique protein docking server, designed to be useful for the experimental biology community. The InterEvDock2 web interface is available at http://bioserv.rpbs.univ-Paris-diderot.fr/services/InterEvDock2/.", "date": "2018-07-02T00:00:00Z", "citationCount": 44, "authors": [ { "name": "Quignot C." }, { "name": "Rey J." }, { "name": "Yu J." }, { "name": "Tuffery P." }, { "name": "Guerois R." }, { "name": "Andreani J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkw340", "pmid": "27131368", "pmcid": "PMC4987904", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "InterEvDock: A docking server to predict the structure of protein-protein interactions using evolutionary information", "abstract": "The structural modeling of protein-protein interactions is key in understanding how cell machineries cross-talk with each other. Molecular docking simulations provide efficient means to explore how two unbound protein structures interact. InterEvDock is a server for protein docking based on a free rigidbody docking strategy. A systematic rigid-body docking search is performed using the FRODOCK program and the resulting models are re-scored with InterEvScore and SOAP-PP statistical potentials. The InterEvScore potential was specifically designed to integrate co-evolutionary information in the docking process. InterEvDock server is thus particularly well suited in case homologous sequences are available for both binding partners. The server returns 10 structures of the most likely consensus models together with 10 predicted residues most likely involved in the interface. In 91% of all complexes tested in the benchmark, at least one residue out of the 10 predicted is involved in the interface, providing useful guidelines for mutagenesis. InterEvDock is able to identify a correct model among the top10 models for 49% of the rigid-body cases with evolutionary information, making it a unique and efficient tool to explore structural interactomes under an evolutionary perspective. The InterEvDock web interface is available at http://bioserv.rpbs.univ-Paris-diderot.fr/services/InterEvDock/.", "date": "2016-01-01T00:00:00Z", "citationCount": 60, "authors": [ { "name": "Yu J." }, { "name": "Vavrusa M." }, { "name": "Andreani J." }, { "name": "Rey J." }, { "name": "Tuffery P." }, { "name": "Guerois R." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/btt260", "pmid": "23652426", "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "InterEvScore: A novel coarse-grained interface scoring function using a multi-body statistical potential coupled to evolution", "abstract": "Motivation: Structural prediction of protein interactions currently remains a challenging but fundamental goal. In particular, progress in scoring functions is critical for the efficient discrimination of near-native interfaces among large sets of decoys. Many functions have been developed using knowledge-based potentials, but few make use of multi-body interactions or evolutionary information, although multi-residue interactions are crucial for protein-protein binding and protein interfaces undergo significant selection pressure to maintain their interactions.Results: This article presents InterEvScore, a novel scoring function using a coarse-grained statistical potential including two- and three-body interactions, which provides each residue with the opportunity to contribute in its most favorable local structural environment. Combination of this potential with evolutionary information considerably improves scoring results on the 54 test cases from the widely used protein docking benchmark for which evolutionary information can be collected. We analyze how our way to include evolutionary information gradually increases the discriminative power of InterEvScore. Comparison with several previously published scoring functions (ZDOCK, ZRANK and SPIDER) shows the significant progress brought by InterEvScore. © 2013 The Author 2013. Published by Oxford University Press. All rights reserved.", "date": "2013-07-15T00:00:00Z", "citationCount": 65, "authors": [ { "name": "Andreani J." }, { "name": "Faure G." }, { "name": "Guerois R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Raphael Guerois", "email": "raphael.guerois@cea.fr", "url": null, "orcidid": "https://orcid.org/0000-0001-5294-2858", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Jessica Andreani", "email": "jessica.andreani@cea.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "reyjul", "additionDate": "2018-07-06T11:57:04Z", "lastUpdate": "2024-11-24T21:00:12.284563Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Housekeeping and Reference Transcript Atlas", "description": "Redefining human and mouse housekeeping genes and candidate reference transcripts by mining massive RNA-seq datasets.\n\nWeb-based tools to search tissue specific housekeeping genes.", "homepage": "http://www.housekeeping.unicamp.br", "biotoolsID": "Housekeeping", "biotoolsCURIE": "biotools:Housekeeping", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" }, { "uri": "http://edamontology.org/operation_3840", "term": "Multilocus sequence typing" }, { "uri": "http://edamontology.org/operation_2424", "term": "Comparison" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" }, { "uri": "http://edamontology.org/topic_0632", "term": "Probes and primers" }, { "uri": "http://edamontology.org/topic_3518", "term": "Microarray experiment" }, { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_3361", "term": "Laboratory techniques" }, { "uri": "http://edamontology.org/topic_3678", "term": "Experimental design and studies" } ], "operatingSystem": [], "language": [ "R" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://www.housekeeping.unicamp.br", "type": [ "Service", "Repository" ], "note": "Database home page" }, { "url": "https://github.com/Bidossessih/HRT_Atlas", "type": [ "Repository" ], "note": "Hrt Atlas Github" } ], "download": [], "documentation": [ { "url": "http://housekeeping.unicamp.br/?about", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkaa609", "pmid": "32663312", "pmcid": "PMC7778946", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "HRT Atlas v1.0 database: Redefining human and mouse housekeeping genes and candidate reference transcripts by mining massive RNA-seq datasets", "abstract": "Housekeeping (HK) genes are constitutively expressed genes that are required for the maintenance of basic cellular functions. Despite their importance in the calibration of gene expression, as well as the understanding of many genomic and evolutionary features, important discrepancies have been observed in studies that previously identified these genes. Here, we present Housekeeping and Reference Transcript Atlas (HRT Atlas v1.0, www.housekeeping.unicamp.br) a web-based database which addresses some of the previously observed limitations in the identification of these genes, and offers a more accurate database of human and mouse HK genes and transcripts. The database was generated by mining massive human and mouse RNA-seq data sets, including 11 281 and 507 high-quality RNA-seq samples from 52 human non-disease tissues/cells and 14 healthy tissues/cells of C57BL/6 wild type mouse, respectively. User can visualize the expression and download lists of 2158 human HK transcripts from 2176 HK genes and 3024 mouse HK transcripts from 3277 mouse HK genes. HRT Atlas also offers the most stable and suitable tissue selective candidate reference transcripts for normalization of qPCR experiments. Specific primers and predicted modifiers of gene expression for some of these HK transcripts are also proposed. HRT Atlas has also been integrated with a regulatory elements resource from Epiregio server.", "date": "2021-01-08T00:00:00Z", "citationCount": 112, "authors": [ { "name": "Hounkpe B.W." }, { "name": "Chenou F." }, { "name": "de Lima F." }, { "name": "de Paula E.V." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Bidossessi Wilfried Hounkpe", "email": "bidossessi1@live.fr", "url": null, "orcidid": "http://orcid.org/0000-0002-9992-1939", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null } ], "owner": "Pub2Tools", "additionDate": "2020-01-09T18:22:25Z", "lastUpdate": "2024-11-24T20:56:06.014004Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Fast-GBS", "description": "Fast-GBS is an analysis toolkit for genotyping-by-sequencing data. Genotyping-by-sequencing (GBS) is a rapid, flexible, low-cost, and robust genotyping method that simultaneously discovers variants and calls genotypes within a broad range of samples. These characteristics make GBS an excellent tool for many applications and research questions from conservation biology to functional genomics in both model and non-model species. Continued improvement of GBS relies on a more comprehensive understanding of data analysis, development of fast and efficient bioinformatics pipelines, accurate missing data imputation, and active post-release support.", "homepage": "https://bitbucket.org/jerlar73/fast-gbs_v2/src/master/", "biotoolsID": "fast-gbs", "biotoolsCURIE": "biotools:fast-gbs", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3557", "term": "Imputation" }, { "uri": "http://edamontology.org/operation_3196", "term": "Genotyping" }, { "uri": "http://edamontology.org/operation_3227", "term": "Variant calling" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://hub.docker.com/repository/docker/jelar5/fast-gbs_v2", "type": "Container file", "note": null, "version": null } ], "documentation": [], "publication": [ { "doi": "10.1139/gen-2020-0077", "pmid": "33006480", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Fast-gbs v2.0: An analysis toolkit for genotyping-by-sequencing data", "abstract": "Genotyping-by-sequencing (GBS) is a rapid, flexible, low-cost, and robust genotyping method that simultaneously discovers variants and calls genotypes within a broad range of samples. These characteristics make GBS an excellent tool for many applications and research questions from conservation biology to functional genomics in both model and non-model species. Continued improvement of GBS relies on a more comprehensive understanding of data analysis, development of fast and efficient bioinformatics pipelines, accurate missing data imputation, and active post-release support. Here, we present the second generation of Fast-GBS (v2.0) that offers several new options (e.g., processing paired-end reads and imputation of missing data) and features (e.g., summary statistics of genotypes) to improve the GBS data analysis process. The performance assessment analysis showed that Fast-GBS v2.0 outperformed other available analytical pipelines, such as GBS-SNP-CROP and Gb-eaSy. Fast-GBS v2.0 provides an analysis platform that can be run with different types of sequencing data, modest computational resources, and allows for missing-data imputation for various species in different contexts.", "date": "2020-01-01T00:00:00Z", "citationCount": 20, "authors": [ { "name": "Torkamaneh D." }, { "name": "Laroche J." }, { "name": "Belzile F." } ], "journal": "Genome" } }, { "doi": "10.1186/s12859-016-1431-9", "pmid": "28049422", "pmcid": "PMC5210301", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Fast-GBS: A new pipeline for the efficient and highly accurate calling of SNPs from genotyping-by-sequencing data", "abstract": "Background: Next-generation sequencing (NGS) technologies have accelerated considerably the investigation into the composition of genomes and their functions. Genotyping-by-sequencing (GBS) is a genotyping approach that makes use of NGS to rapidly and economically scan a genome. It has been shown to allow the simultaneous discovery and genotyping of thousands to millions of SNPs across a wide range of species. For most users, the main challenge in GBS is the bioinformatics analysis of the large amount of sequence information derived from sequencing GBS libraries in view of calling alleles at SNP loci. Herein we describe a new GBS bioinformatics pipeline, Fast-GBS, designed to provide highly accurate genotyping, to require modest computing resources and to offer ease of use. Results: Fast-GBS is built upon standard bioinformatics language and file formats, is capable of handling data from different sequencing platforms, is capable of detecting different kinds of variants (SNPs, MNPs, and Indels). To illustrate its performance, we called variants in three collections of samples (soybean, barley, and potato) that cover a range of different genome sizes, levels of genome complexity, and ploidy. Within these small sets of samples, we called 35 k, 32 k and 38 k SNPs for soybean, barley and potato, respectively. To assess genotype accuracy, we compared these GBS-derived SNP genotypes with independent data sets obtained from whole-genome sequencing or SNP arrays. This analysis yielded estimated accuracies of 98.7, 95.2, and 94% for soybean, barley, and potato, respectively. Conclusions: We conclude that Fast-GBS provides a highly efficient and reliable tool for calling SNPs from GBS data.", "date": "2017-01-03T00:00:00Z", "citationCount": 88, "authors": [ { "name": "Torkamaneh D." }, { "name": "Laroche J." }, { "name": "Bastien M." }, { "name": "Abed A." }, { "name": "Belzile F." } ], "journal": "BMC Bioinformatics" } } ], "credit": [], "owner": "Kigaard", "additionDate": "2021-01-18T11:25:29Z", "lastUpdate": "2024-11-24T20:39:39.982654Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PredictSNP2", "description": "A consensus classifier that combines five of the top performing tools (CADD, DANN, FATHMM, FunSeq2 and GWAVA) for the evaluation of pathogenic effect of SNPs within the human genome. The obtained results are provided together with annotations extracted from dbSNP, GenBank, Clinvar, OMIM, RegulomeDB, HaploReg, UCSC and Ensembl databases.", "homepage": "https://loschmidt.chemi.muni.cz/predictsnp2", "biotoolsID": "predictsnp2", "biotoolsCURIE": "biotools:predictsnp2", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3672", "term": "Gene functional annotation" }, { "uri": "http://edamontology.org/operation_3225", "term": "Variant classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [ { "uri": "http://edamontology.org/format_3019", "term": "GVF" }, { "uri": "http://edamontology.org/format_3016", "term": "VCF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [ { "uri": "http://edamontology.org/format_3016", "term": "VCF" }, { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] } ], "note": "VCF file containing scores and PDF file containing scores and database links", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_2533", "term": "DNA mutation" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript", "Java" ], "license": "Proprietary", "collectionID": [ "Czech Republic", "Rare Disease", "ELIXIR-CZ" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://loschmidt.chemi.muni.cz/peg/software/predictsnp2-standalone/", "type": "Downloads page", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://loschmidt.chemi.muni.cz/predictsnp2/docs/userguide.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1371/journal.pcbi.1004962", "pmid": "27224906", "pmcid": "PMC4880439", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions", "abstract": "An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools’ predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2.", "date": "2016-05-01T00:00:00Z", "citationCount": 143, "authors": [ { "name": "Bendl J." }, { "name": "Musil M." }, { "name": "Stourac J." }, { "name": "Zendulka J." }, { "name": "Damborsky J." }, { "name": "Brezovsky J." } ], "journal": "PLoS Computational Biology" } } ], "credit": [ { "name": "Jaroslav Bendl", "email": "jaroslav.bendl@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0001-9989-2720", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jan Stourac", "email": "stourac.jan@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-3139-3700", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Support" ], "note": null }, { "name": "Milos Musil", "email": "xmusil46@stud.fit.vutbr.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-9373-7930", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jan Brezovsky", "email": "brezovsky@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-9677-5078", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jiri Damborsky", "email": "1441@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-7848-8216", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Eric D. Wieben", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jaroslav Zendulka", "email": "zendulka@fit.vut.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-8718-7493", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Antonin Pavelka", "email": "99207@mail.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Loschmidt Laboratories", "email": null, "url": "https://loschmidt.chemi.muni.cz/peg/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Masaryk University, Brno, Czech Republic", "email": null, "url": "https://www.muni.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "International Centre for Clinical Research, Brno, Czech Republic", "email": null, "url": "https://www.fnusa-icrc.org/en/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Brno University of Technology, Brno, Czech Republic", "email": null, "url": "https://www.vutbr.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "ELIXIR-CZ", "email": null, "url": "https://www.elixir-czech.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Provider" ], "note": null }, { "name": "PredictSNP team", "email": "predictsnp@sci.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "European Regional Development Fund", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "European Social Fund", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Grant Agency of the Czech Republic", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Ministry of Education of the Czech Republic", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Brno University of Technology", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null } ], "owner": "Loschmidt Laboratories", "additionDate": "2016-06-30T09:32:44Z", "lastUpdate": "2024-11-24T20:23:08.475881Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "CaverDock", "description": "Performs rapid analysis of transport processes in proteins. It models the transportation of a ligand from outside environment into the protein active or binding site and vice versa. It implements a novel algorithm to produce contiguous ligand trajectory and estimation of a binding energy along the pathway. The current version uses CAVER for pathway identification and heavily modified Autodock Vina as a docking engine.", "homepage": "https://loschmidt.chemi.muni.cz/caverdock/", "biotoolsID": "caverdock", "biotoolsCURIE": "biotools:caverdock", "version": [ "1.0", "1.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0482", "term": "Protein-ligand docking" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_1463", "term": "Small molecule structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1537", "term": "Protein structure report" }, "format": [ { "uri": "http://edamontology.org/format_1957", "term": "raw" }, { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "note": "trajectory of ligand passing through protein tunnel and its energy", "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++", "Python" ], "license": "Proprietary", "collectionID": [ "CAVER", "ELIXIR-CZ" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": null, "elixirPlatform": [ "Tools" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [ { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-ubuntu-14.04.tar.gz", "type": "Binaries", "note": "v1.0, Ubuntu 14.04", "version": "1.0" }, { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-ubuntu-16.04.tar.gz", "type": "Binaries", "note": "v1.0, Ubuntu 16.04", "version": "1.0" }, { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-1.1-ubuntu-16.04.tar.xz", "type": "Binaries", "note": "v1.1, Ubuntu 16.04", "version": "1.1" }, { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-1.1-ubuntu-18.04.tar.xz", "type": "Binaries", "note": "v1.1, Ubuntu 18.04", "version": "1.1" } ], "documentation": [ { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/manual.pdf", "type": [ "User manual" ], "note": "version 1.0" }, { "url": "https://www.fi.muni.cz/~xfilipov/caverdock/manual-1.1.pdf", "type": [ "User manual" ], "note": "version 1.1" } ], "publication": [ { "doi": "10.1093/bioinformatics/btz386", "pmid": "31077297", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "CaverDock: A molecular docking-based tool to analyse ligand transport through protein tunnels and channels", "abstract": "Motivation: Protein tunnels and channels are key transport pathways that allow ligands to pass between proteins' external and internal environments. These functionally important structural features warrant detailed attention. It is difficult to study the ligand binding and unbinding processes experimentally, while molecular dynamics simulations can be time-consuming and computationally demanding. Results: CaverDock is a new software tool for analysing the ligand passage through the biomolecules. The method uses the optimized docking algorithm of AutoDock Vina for ligand placement docking and implements a parallel heuristic algorithm to search the space of possible trajectories. The duration of the simulations takes from minutes to a few hours. Here we describe the implementation of the method and demonstrate CaverDock's usability by: (i) comparison of the results with other available tools, (ii) determination of the robustness with large ensembles of ligands and (iii) the analysis and comparison of the ligand trajectories in engineered tunnels. Thorough testing confirms that CaverDock is applicable for the fast analysis of ligand binding and unbinding in fundamental enzymology and protein engineering. Availability and implementation: User guide and binaries for Ubuntu are freely available for non-commercial use at https://loschmidt.chemi.muni.cz/caverdock/. The web implementation is available at https://loschmidt.chemi.muni.cz/caverweb/. The source code is available upon request. Supplementary information: Supplementary data are available at Bioinformatics online.", "date": "2019-12-01T00:00:00Z", "citationCount": 55, "authors": [ { "name": "Vavra O." }, { "name": "Filipovic J." }, { "name": "Plhak J." }, { "name": "Bednar D." }, { "name": "Marques S.M." }, { "name": "Brezovsky J." }, { "name": "Stourac J." }, { "name": "Matyska L." }, { "name": "Damborsky J." } ], "journal": "Bioinformatics" } }, { "doi": "10.1109/tcbb.2019.2907492", "pmid": "30932844", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "CaverDock: A Novel Method for the Fast Analysis of Ligand Transport", "abstract": "Here we present a novel method for the analysis of transport processes in proteins and its implementation called CaverDock. Our method is based on a modified molecular docking algorithm. It iteratively places the ligand along the access tunnel in such a way that the ligand movement is contiguous and the energy is minimized. The result of CaverDock calculation is a ligand trajectory and an energy profile of transport process. CaverDock uses the modified docking program Autodock Vina for molecular docking and implements a parallel heuristic algorithm for searching the space of possible trajectories. Our method lies in between the geometrical approaches and molecular dynamics simulations. Contrary to the geometrical methods, it provides an evaluation of chemical forces. However, it is far less computationally demanding and easier to set up compared to molecular dynamics simulations. CaverDock will find a broad use in the fields of computational enzymology, drug design, and protein engineering. The software is available free of charge to the academic users at https://loschmidt.chemi.muni.cz/caverdock/.", "date": "2020-09-01T00:00:00Z", "citationCount": 26, "authors": [ { "name": "Filipovic J." }, { "name": "Vavra O." }, { "name": "Plhak J." }, { "name": "Bednar D." }, { "name": "Marques S.M." }, { "name": "Brezovsky J." }, { "name": "Matyska L." }, { "name": "Damborsk J." } ], "journal": "IEEE/ACM Transactions on Computational Biology and Bioinformatics" } } ], "credit": [ { "name": "Jiri Filipovic", "email": "fila@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-5703-9673", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Ondrej Vavra", "email": "o.vavra@mail.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jan Plhak", "email": "408420@mail.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "David Bednar", "email": "222755@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-6803-0340", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Sergio Marques", "email": "smar96@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0002-6281-7505", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jan Brezovsky", "email": "brezovsky@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-9677-5078", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jan Stourac", "email": "stourac.jan@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-3139-3700", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Support" ], "note": null }, { "name": "Ludek Matyska", "email": "Ludek.Matyska@muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-6399-5453", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jiri Damborsky", "email": "1441@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-7848-8216", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Loschmidt Laboratories", "email": null, "url": "https://loschmidt.chemi.muni.cz/peg/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Masaryk University, Brno, Czech Republic", "email": null, "url": "https://www.muni.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "International Centre for Clinical Research, Brno, Czech Republic", "email": null, "url": "https://www.fnusa-icrc.org/en/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "ELIXIR-CZ", "email": null, "url": "https://www.elixir-czech.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Provider" ], "note": null }, { "name": "CaverDock team", "email": "caver@caver.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "European Commission", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Czech Science Foundation", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Brno City Municipality", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null } ], "owner": "Loschmidt Laboratories", "additionDate": "2018-04-06T08:55:47Z", "lastUpdate": "2024-11-24T20:23:05.902530Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-CZ" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PredictSNP", "description": "A consensus classifier that combines six of the top performing tools for the prediction of the effects of mutation on protein function. The obtained results are provided together with annotations extracted from the Protein Mutant Database and the UniProt database.", "homepage": "https://loschmidt.chemi.muni.cz/predictsnp1", "biotoolsID": "predictsnp", "biotoolsCURIE": "biotools:predictsnp", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "mapp", "type": "uses" }, { "biotoolsID": "nssnpanalyzer", "type": "uses" }, { "biotoolsID": "panther", "type": "uses" }, { "biotoolsID": "phd-snp", "type": "uses" }, { "biotoolsID": "polyphen", "type": "uses" }, { "biotoolsID": "polyphen-2", "type": "uses" }, { "biotoolsID": "sift", "type": "uses" }, { "biotoolsID": "snap", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0331", "term": "Variant effect prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1277", "term": "Protein features" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_2291", "term": "UniProt ID" }, "format": [] } ], "note": "Prediction of the effect of amino acid substitution on protein function", "cmd": null } ], "toolType": [ "Command-line tool", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_2885", "term": "DNA polymorphism" }, { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_3053", "term": "Genetics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript", "Java", "Python" ], "license": "Proprietary", "collectionID": [ "Czech Republic", "Rare Disease", "ELIXIR-CZ" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://loschmidt.chemi.muni.cz/predictsnp1/docs/predictsnp-1.0.tar.gz", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://loschmidt.chemi.muni.cz/predictsnp1/docs/USER_GUIDE.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1371/journal.pcbi.1003440", "pmid": "24453961", "pmcid": "PMC3894168", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations", "abstract": "Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp. © 2014 Bendl et al.", "date": "2014-01-01T00:00:00Z", "citationCount": 595, "authors": [ { "name": "Bendl J." }, { "name": "Stourac J." }, { "name": "Salanda O." }, { "name": "Pavelka A." }, { "name": "Wieben E.D." }, { "name": "Zendulka J." }, { "name": "Brezovsky J." }, { "name": "Damborsky J." } ], "journal": "PLoS Computational Biology" } } ], "credit": [ { "name": "Jaroslav Bendl", "email": "jaroslav.bendl@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0001-9989-2720", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jan Stourac", "email": "stourac.jan@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-3139-3700", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Support" ], "note": null }, { "name": "Ondrej Salanda", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jan Brezovsky", "email": "brezovsky@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-9677-5078", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jiri Damborsky", "email": "1441@mail.muni.cz", "url": null, "orcidid": "https://orcid.org/0000-0002-7848-8216", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Eric D. Wieben", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Jaroslav Zendulka", "email": "zendulka@fit.vut.cz", "url": null, "orcidid": "https://orcid.org/0000-0001-8718-7493", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Antonin Pavelka", "email": "99207@mail.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Loschmidt Laboratories", "email": null, "url": "https://loschmidt.chemi.muni.cz/peg/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Masaryk University, Brno, Czech Republic", "email": null, "url": "https://www.muni.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "International Centre for Clinical Research, Brno, Czech Republic", "email": null, "url": "https://www.fnusa-icrc.org/en/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Brno University of Technology, Brno, Czech Republic", "email": null, "url": "https://www.vutbr.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Mayo Clinic, Rochester, New York, United States of America", "email": null, "url": "https://www.mayoclinic.org/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "ELIXIR-CZ", "email": null, "url": "https://www.elixir-czech.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Provider" ], "note": null }, { "name": "PredictSNP team", "email": "predictsnp@sci.muni.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "European Regional Development Fund", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "European Social Fund", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Grant Agency of the Czech Republic", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Ministry of Education of the Czech Republic", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": "Brno University of Technology", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null } ], "owner": "Loschmidt Laboratories", "additionDate": "2015-11-07T20:40:08Z", "lastUpdate": "2024-11-24T20:22:54.522074Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "AraQTL", "description": "AraQTL is the A.thaliana workbench and database for eQTL analysis.\nIt allows easy access to the data of all published Arabidopsis thaliana genetical genomics experiments.", "homepage": "https://www.bioinformatics.nl/AraQTL", "biotoolsID": "araqtl", "biotoolsCURIE": "biotools:araqtl", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3232", "term": "Gene expression QTL analysis" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0282", "term": "Genetic mapping" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3360", "term": "Biomarkers" }, { "uri": "http://edamontology.org/topic_3517", "term": "GWAS study" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1111/tpj.13457", "pmid": "27995664", "pmcid": null, "type": [], "version": "1.0", "note": null, "metadata": { "title": "AraQTL – workbench and archive for systems genetics in Arabidopsis thaliana", "abstract": "Genetical genomics studies uncover genome-wide genetic interactions between genes and their transcriptional regulators. High-throughput measurement of gene expression in recombinant inbred line populations has enabled investigation of the genetic architecture of variation in gene expression. This has the potential to enrich our understanding of the molecular mechanisms affected by and underlying natural variation. Moreover, it contributes to the systems biology of natural variation, as a substantial number of experiments have resulted in a valuable amount of interconnectable phenotypic, molecular and genotypic data. A number of genetical genomics studies have been published for Arabidopsis thaliana, uncovering many expression quantitative trait loci (eQTLs). However, these complex data are not easily accessible to the plant research community, leaving most of the valuable genetic interactions unexplored as cross-analysis of these studies is a major effort. We address this problem with AraQTL (http://www.bioinformatics.nl/Ara QTL/), an easily accessible workbench and database for comparative analysis and meta-analysis of all published Arabidopsis eQTL datasets. AraQTL provides a workbench for comparing, re-using and extending upon the results of these experiments. For example, one can easily screen a physical region for specific local eQTLs that could harbour candidate genes for phenotypic QTLs, or detect gene-by-environment interactions by comparing eQTLs under different conditions.", "date": "2017-03-01T00:00:00Z", "citationCount": 15, "authors": [ { "name": "Nijveen H." }, { "name": "Ligterink W." }, { "name": "Keurentjes J.J.B." }, { "name": "Loudet O." }, { "name": "Long J." }, { "name": "Sterken M.G." }, { "name": "Prins P." }, { "name": "Hilhorst H.W." }, { "name": "de Ridder D." }, { "name": "Kammenga J.E." }, { "name": "Snoek B.L." } ], "journal": "Plant Journal" } } ], "credit": [ { "name": "Harm Nijveen", "email": "harm.nijveen@wur.nl", "url": null, "orcidid": "https://orcid.org/0000-0002-9167-4945", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Wilco Ligterink", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-0228-169X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Joost J. B. Keurentjes", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-8918-0711", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Olivier Loudet", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-3717-0137", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Jiao Long", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Mark G. Sterken", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-7119-6213", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Pjotr Prins", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Henk W. Hilhorst", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-6743-583X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Dick de Ridder", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-4944-4310", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Jan E. Kammenga", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Basten L. Snoek", "email": "basten.snoek@wur.nl", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "marieBvr", "additionDate": "2021-03-23T16:13:44Z", "lastUpdate": "2024-11-24T20:21:13.730744Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "tripr", "description": "T-cell Receptor/Immunoglobulin Profiler (TRIP)", "homepage": "https://github.com/BiodataAnalysisGroup/TRIP", "biotoolsID": "TRIP_-_T-cell_Receptor_Immunoglobulin_Profiler", "biotoolsCURIE": "biotools:TRIP_-_T-cell_Receptor_Immunoglobulin_Profiler", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2403", "term": "Sequence analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_2830", "term": "Immunoproteins and antigens" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Greece" ], "elixirCommunity": [], "link": [ { "url": "https://www.bioconductor.org/packages/devel/bioc/html/tripr.html", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://www.bioconductor.org/packages/devel/bioc/manuals/tripr/man/tripr.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1186/s12859-020-03669-1", "pmid": "32993478", "pmcid": "PMC7525938", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "TRIP - T cell receptor/immunoglobulin profiler", "abstract": "Background: Antigen receptors are characterized by an extreme diversity of specificities, which poses major computational and analytical challenges, particularly in the era of high-throughput immunoprofiling by next generation sequencing (NGS). The T cell Receptor/Immunoglobulin Profiler (TRIP) tool offers the opportunity for an in-depth analysis based on the processing of the output files of the IMGT/HighV-Quest tool, a standard in NGS immunoprofiling, through a number of interoperable modules. These provide detailed information about antigen receptor gene rearrangements, including variable (V), diversity (D) and joining (J) gene usage, CDR3 amino acid and nucleotide composition and clonality of both T cell receptors (TR) and B cell receptor immunoglobulins (BcR IG), and characteristics of the somatic hypermutation within the BcR IG genes. TRIP is a web application implemented in R shiny. Results: Two sets of experiments have been performed in order to evaluate the efficiency and performance of the TRIP tool. The first used a number of synthetic datasets, ranging from 250k to 1M sequences, and established the linear response time of the tool (about 6 h for 1M sequences processed through the entire BcR IG data pipeline). The reproducibility of the tool was tested comparing the results produced by the main TRIP workflow with the results from a previous pipeline used on the Galaxy platform. As expected, no significant differences were noted between the two tools; although the preselection process seems to be stricter within the TRIP pipeline, about 0.1% more rearrangements were filtered out, with no impact on the final results. Conclusions: TRIP is a software framework that provides analytical services on antigen receptor gene sequence data. It is accurate and contains functions for data wrangling, cleaning, analysis and visualization, enabling the user to build a pipeline tailored to their needs. TRIP is publicly available at https://bio.tools/TRIP_-_T-cell_Receptor_Immunoglobulin_Profiler.", "date": "2020-09-29T00:00:00Z", "citationCount": 11, "authors": [ { "name": "Kotouza M.T." }, { "name": "Gemenetzi K." }, { "name": "Galigalidou C." }, { "name": "Vlachonikola E." }, { "name": "Pechlivanis N." }, { "name": "Agathangelidis A." }, { "name": "Sandaltzopoulos R." }, { "name": "Mitkas P.A." }, { "name": "Stamatopoulos K." }, { "name": "Chatzidimitriou A." }, { "name": "Psomopoulos F.E." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Fotis E. Psomopoulos", "email": "fpsom@certh.gr", "url": "https://biodataanalysisgroup.github.io/", "orcidid": "https://orcid.org/0000-0002-0222-4273", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Maria Th. Kotouza", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Katerina Gemenetzi", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Chrysi Galigalidou", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "fpsom", "additionDate": "2020-02-21T13:12:50Z", "lastUpdate": "2024-11-24T15:49:18.952349Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "tripr", "description": "T-cell Receptor/Immunoglobulin Profiler (TRIP)", "homepage": "https://github.com/BiodataAnalysisGroup/TRIP", "biotoolsID": "tripr", "biotoolsCURIE": "biotools:tripr", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2403", "term": "Sequence analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_2830", "term": "Immunoproteins and antigens" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Greece" ], "elixirCommunity": [], "link": [ { "url": "https://www.bioconductor.org/packages/devel/bioc/html/tripr.html", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://www.bioconductor.org/packages/devel/bioc/manuals/tripr/man/tripr.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1186/s12859-020-03669-1", "pmid": "32993478", "pmcid": "PMC7525938", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "TRIP - T cell receptor/immunoglobulin profiler", "abstract": "Background: Antigen receptors are characterized by an extreme diversity of specificities, which poses major computational and analytical challenges, particularly in the era of high-throughput immunoprofiling by next generation sequencing (NGS). The T cell Receptor/Immunoglobulin Profiler (TRIP) tool offers the opportunity for an in-depth analysis based on the processing of the output files of the IMGT/HighV-Quest tool, a standard in NGS immunoprofiling, through a number of interoperable modules. These provide detailed information about antigen receptor gene rearrangements, including variable (V), diversity (D) and joining (J) gene usage, CDR3 amino acid and nucleotide composition and clonality of both T cell receptors (TR) and B cell receptor immunoglobulins (BcR IG), and characteristics of the somatic hypermutation within the BcR IG genes. TRIP is a web application implemented in R shiny. Results: Two sets of experiments have been performed in order to evaluate the efficiency and performance of the TRIP tool. The first used a number of synthetic datasets, ranging from 250k to 1M sequences, and established the linear response time of the tool (about 6 h for 1M sequences processed through the entire BcR IG data pipeline). The reproducibility of the tool was tested comparing the results produced by the main TRIP workflow with the results from a previous pipeline used on the Galaxy platform. As expected, no significant differences were noted between the two tools; although the preselection process seems to be stricter within the TRIP pipeline, about 0.1% more rearrangements were filtered out, with no impact on the final results. Conclusions: TRIP is a software framework that provides analytical services on antigen receptor gene sequence data. It is accurate and contains functions for data wrangling, cleaning, analysis and visualization, enabling the user to build a pipeline tailored to their needs. TRIP is publicly available at https://bio.tools/TRIP_-_T-cell_Receptor_Immunoglobulin_Profiler.", "date": "2020-09-29T00:00:00Z", "citationCount": 11, "authors": [ { "name": "Kotouza M.T." }, { "name": "Gemenetzi K." }, { "name": "Galigalidou C." }, { "name": "Vlachonikola E." }, { "name": "Pechlivanis N." }, { "name": "Agathangelidis A." }, { "name": "Sandaltzopoulos R." }, { "name": "Mitkas P.A." }, { "name": "Stamatopoulos K." }, { "name": "Chatzidimitriou A." }, { "name": "Psomopoulos F.E." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Fotis E. Psomopoulos", "email": "fpsom@certh.gr", "url": "https://biodataanalysisgroup.github.io/", "orcidid": "https://orcid.org/0000-0002-0222-4273", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Maria Th. Kotouza", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Katerina Gemenetzi", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Chrysi Galigalidou", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "Jennifer", "additionDate": "2022-08-16T14:46:38.276886Z", "lastUpdate": "2024-11-24T15:49:17.603843Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "bamtocov", "description": "Tools to extract coverage informations from BAM (and CRAM) files, based on the covtobed algorithm that supports stranded coverage and physical coverage, input from streams and uses a memory-efficient algorithm.", "homepage": "https://telatin.github.io/bamtocov/", "biotoolsID": "bamtocov", "biotoolsCURIE": "biotools:bamtocov", "version": [ "2.5.0", "2.7.0", "2.8.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0260", "term": "Sequence alignment conversion" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" }, { "uri": "http://edamontology.org/format_3462", "term": "CRAM" } ] }, { "data": { "uri": "http://edamontology.org/data_3002", "term": "Annotation track" }, "format": [ { "uri": "http://edamontology.org/format_3003", "term": "BED" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3002", "term": "Annotation track" }, "format": [ { "uri": "http://edamontology.org/format_3583", "term": "bedgraph" }, { "uri": "http://edamontology.org/format_3005", "term": "WIG" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [], "operatingSystem": [ "Linux", "Mac" ], "language": [ "C" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://telatin.github.io/bamtocov/", "type": [ "Other" ], "note": null }, { "url": "https://github.com/telatin/bamtocov", "type": [ "Repository" ], "note": null }, { "url": "https://anaconda.org/bioconda/bamtocov", "type": [ "Software catalogue" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1101/2021.11.12.466787", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": null, "note": "Preprint hosted by biorXiv", "metadata": null }, { "doi": "10.1093/bioinformatics/btac125", "pmid": "35199151", "pmcid": "PMC9048650", "type": [], "version": "1.0", "note": "Bioinformatics Application note on BamToCov", "metadata": { "title": "BamToCov: An efficient toolkit for sequence coverage calculations", "abstract": "Motivation: Many genomics applications require the computation of nucleotide coverage of a reference genome or the ability to determine how many reads map to a reference region. Results: BamToCov is a toolkit for rapid and flexible coverage computation that relies on the most memory efficient algorithm and is designed for integration in pipelines, given its ability to read alignment files from streams. The tools in the suite can process sorted BAM or CRAM files, allowing the user to extract coverage information via different filtering approaches and to save the output in different formats (BED, Wig or counts). The BamToCov algorithm can also handle strand-specific and/or physical coverage analyses.", "date": "2022-05-01T00:00:00Z", "citationCount": 11, "authors": [ { "name": "Birolo G." }, { "name": "Telatin A." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Andrea Telatin", "email": null, "url": "https://github.com/telatin", "orcidid": "https://orcid.org/0000-0001-7619-281X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Giovanni Birolo", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-0160-9312", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "telatin", "additionDate": "2022-01-25T09:42:42.478699Z", "lastUpdate": "2024-11-24T15:31:24.841052Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Cordax", "description": "The amyloid conformation can be adopted by a variety of sequences, but the precise boundaries of amyloid sequence space are still unclear. The currently charted amyloid sequence space is strongly biased towards hydrophobic, beta-sheet prone sequences that form the core of globular proteins and by Q/N/Y rich yeast prions. Here, we took advantage of the increasing amount of high-resolution structural information on amyloid cores currently available in the protein databank to implement a machine learning approach, named Cordax (https://cordax.switchlab.org), that explores amyloid sequence beyond its current boundaries.", "homepage": "https://cordax.switchlab.org", "biotoolsID": "cordax", "biotoolsCURIE": "biotools:cordax", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [ "VIB", "KU Leuven" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1038/s41467-020-17207-3", "pmid": "32620861", "pmcid": "PMC7335209", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities", "abstract": "The amyloid conformation can be adopted by a variety of sequences, but the precise boundaries of amyloid sequence space are still unclear. The currently charted amyloid sequence space is strongly biased towards hydrophobic, beta-sheet prone sequences that form the core of globular proteins and by Q/N/Y rich yeast prions. Here, we took advantage of the increasing amount of high-resolution structural information on amyloid cores currently available in the protein databank to implement a machine learning approach, named Cordax (https://cordax.switchlab.org), that explores amyloid sequence beyond its current boundaries. Clustering by t-Distributed Stochastic Neighbour Embedding (t-SNE) shows how our approach resulted in an expansion away from hydrophobic amyloid sequences towards clusters of lower aliphatic content and higher charge, or regions of helical and disordered propensities. These clusters uncouple amyloid propensity from solubility representing sequence flavours compatible with surface-exposed patches in globular proteins, functional amyloids or sequences associated to liquid-liquid phase transitions.", "date": "2020-12-01T00:00:00Z", "citationCount": 54, "authors": [ { "name": "Louros N." }, { "name": "Orlando G." }, { "name": "De Vleeschouwer M." }, { "name": "Rousseau F." }, { "name": "Schymkowitz J." } ], "journal": "Nature Communications" } } ], "credit": [ { "name": "Joost Schymkowitz", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-2020-0168", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact" ], "note": null } ], "owner": "bits@vib.be", "additionDate": "2020-12-10T17:29:48Z", "lastUpdate": "2024-11-24T15:19:34.365901Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PDBinder", "description": "PDBinder is a bioinformatic method for the prediction of small ligand binding sites in protein structures", "homepage": "http://cbm.bio.uniroma2.it/pdbinder/", "biotoolsID": "pdbinder", "biotoolsCURIE": "biotools:pdbinder", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3897", "term": "Ligand-binding site prediction" }, { "uri": "http://edamontology.org/operation_2464", "term": "Protein-protein binding site prediction" }, { "uri": "http://edamontology.org/operation_0420", "term": "Nucleic acids-binding site prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1208", "term": "protein" } ] }, { "data": { "uri": "http://edamontology.org/data_1277", "term": "Protein features" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3534", "term": "Protein binding sites" }, { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0082", "term": "Structure prediction" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/1471-2105-13-s4-s17", "pmid": "22536963", "pmcid": "PMC3434446", "type": [ "Method" ], "version": "1.0", "note": null, "metadata": { "title": "Identification of binding pockets in protein structures using a knowledge-based potential derived from local structural similarities", "abstract": "Background: The identification of ligand binding sites is a key task in the annotation of proteins with known structure but uncharacterized function. Here we describe a knowledge-based method exploiting the observation that unrelated binding sites share small structural motifs that bind the same chemical fragments irrespective of the nature of the ligand as a whole.Results: PDBinder compares a query protein against a library of binding and non-binding protein surface regions derived from the PDB. The results of the comparison are used to derive a propensity value for each residue which is correlated with the likelihood that the residue is part of a ligand binding site. The method was applied to two different problems: i) the prediction of ligand binding residues and ii) the identification of which surface cleft harbours the binding site. In both cases PDBinder performed consistently better than existing methods.PDBinder has been trained on a non-redundant set of 1356 high-quality protein-ligand complexes and tested on a set of 239 holo and apo complex pairs. We obtained an MCC of 0.313 on the holo set with a PPV of 0.413 while on the apo set we achieved an MCC of 0.271 and a PPV of 0.372.Conclusions: We show that PDBinder performs better than existing methods. The good performance on the unbound proteins is extremely important for real-world applications where the location of the binding site is unknown. Moreover, since our approach is orthogonal to those used in other programs, the PDBinder propensity value can be integrated in other algorithms further increasing the final performance. © 2012 Bianchi et al.; licensee BioMed Central Ltd.", "date": "2012-03-28T00:00:00Z", "citationCount": 16, "authors": [ { "name": "Bianchi V." }, { "name": "Gherardini P.F." }, { "name": "Helmer-Citterich M." }, { "name": "Ausiello G." } ], "journal": "BMC Bioinformatics" } } ], "credit": [], "owner": "HelmerCitterich", "additionDate": "2020-07-04T14:19:43Z", "lastUpdate": "2024-11-24T15:18:14.668324Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Plant PTM Viewer", "description": "The Plant PTM Viewer is an integrative PTM resource that comprises approximately 370 000 PTM sites for 19 types of protein modifications in plant proteins from five different species.", "homepage": "http://www.psb.ugent.be/PlantPTMViewer", "biotoolsID": "plant_ptm_viewer", "biotoolsCURIE": "biotools:plant_ptm_viewer", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3645", "term": "PTM identification" }, { "uri": "http://edamontology.org/operation_0417", "term": "PTM site prediction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0601", "term": "Protein modifications" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" } ], "operatingSystem": [], "language": [ "JavaScript" ], "license": "Not licensed", "collectionID": [ "VIB", "UGent", "BIG N2N" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Belgium" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://www.psb.ugent.be/webtools/ptm-viewer/tutorial.php", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1111/tpj.14345", "pmid": "31004550", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "The Plant PTM Viewer, a central resource for exploring plant protein modifications", "abstract": "Post-translational modifications (PTMs) of proteins are central in any kind of cellular signaling. Modern mass spectrometry technologies enable comprehensive identification and quantification of various PTMs. Given the increased numbers and types of mapped protein modifications, a database is necessary that simultaneously integrates and compares site-specific information for different PTMs, especially in plants for which the available PTM data are poorly catalogued. Here, we present the Plant PTM Viewer (http://www.psb.ugent.be/PlantPTMViewer), an integrative PTM resource that comprises approximately 370 000 PTM sites for 19 types of protein modifications in plant proteins from five different species. The Plant PTM Viewer provides the user with a protein sequence overview in which the experimentally evidenced PTMs are highlighted together with an estimate of the confidence by which the modified peptides and, if possible, the actual modification sites were identified and with functional protein domains or active site residues. The PTM sequence search tool can query PTM combinations in specific protein sequences, whereas the PTM BLAST tool searches for modified protein sequences to detect conserved PTMs in homologous sequences. Taken together, these tools help to assume the role and potential interplay of PTMs in specific proteins or within a broader systems biology context. The Plant PTM Viewer is an open repository that allows the submission of mass spectrometry-based PTM data to remain at pace with future PTM plant studies.", "date": "2019-01-01T00:00:00Z", "citationCount": 89, "authors": [ { "name": "Willems P." }, { "name": "Horne A." }, { "name": "Van Parys T." }, { "name": "Goormachtig S." }, { "name": "De Smet I." }, { "name": "Botzki A." }, { "name": "Van Breusegem F." }, { "name": "Gevaert K." } ], "journal": "Plant Journal" } } ], "credit": [ { "name": "Patrick Willems", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Provider", "Primary contact" ], "note": null }, { "name": "Thomas Van Parys", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null }, { "name": "Alison Horne", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null } ], "owner": "bits@vib.be", "additionDate": "2020-08-11T18:06:30Z", "lastUpdate": "2024-11-24T15:18:08.021106Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Beyondcell", "description": "Beyondcell is a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq data and proposing cancer-specific treatments.", "homepage": "https://github.com/cnio-bu/beyondcell", "biotoolsID": "beyondcell", "biotoolsCURIE": "biotools:beyondcell", "version": [ "2.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3223", "term": "Differential gene expression profiling" }, { "uri": "http://edamontology.org/operation_4009", "term": "Small molecule design" }, { "uri": "http://edamontology.org/operation_0313", "term": "Expression profile clustering" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3112", "term": "Gene expression matrix" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_0928", "term": "Gene expression profile" }, "format": [ { "uri": "http://edamontology.org/format_1915", "term": "Format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0951", "term": "Statistical estimate score" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3768", "term": "Clustered expression profiles" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1621", "term": "Pharmacogenomic test report" }, "format": [] } ], "note": "Beyondcell can make use of custom gene expression profiles on top of its own catalogue of drug related signatures. Beyondcell allows the user to input a GMT file containing the functional pathways/signatures of interest as well as numeric matrices containing a ranking\ncriteria such as the t-statistic or logFoldChange.", "cmd": null } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_0208", "term": "Pharmacogenomics" }, { "uri": "http://edamontology.org/topic_2640", "term": "Oncology" }, { "uri": "http://edamontology.org/topic_2229", "term": "Cell biology" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "R" ], "license": "Other", "collectionID": [ "IMPaCT-Data" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://gitlab.com/bu_cnio/beyondcell/-/issues?sort=updated_desc&state=opened", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://gitlab.com/bu_cnio/beyondcell/-/archive/master/beyondcell-master.zip", "type": "Source code", "note": "Source code for the current software version", "version": "1.3.3." }, { "url": "https://anaconda.org/bioconda/r-beyondcell", "type": "Software package", "note": "Conda package for the current software version.", "version": "1.3.3" } ], "documentation": [ { "url": "https://gitlab.com/bu_cnio/beyondcell/-/tree/master/tutorial/analysis_workflow", "type": [ "Quick start guide" ], "note": null }, { "url": "https://gitlab.com/bu_cnio/beyondcell/-/tree/master/tutorial/analysis_workflow", "type": [ "Installation instructions" ], "note": null }, { "url": "https://gitlab.com/bu_cnio/beyondcell/-/tree/master/tutorial/analysis_workflow", "type": [ "Citation instructions" ], "note": null }, { "url": "https://gitlab.com/bu_cnio/beyondcell/-/blob/master/CHANGELOG.md", "type": [ "Release notes" ], "note": null } ], "publication": [ { "doi": "10.1101/2021.04.08.438954", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": "Publication about the methodology and its application in a variety of experimental models, from cancer cell lines to human data.", "metadata": null } ], "credit": [ { "name": "Dr. Fátima Al-Shahrour", "email": "falshahrour@cnio.es", "url": null, "orcidid": "https://orcid.org/0000-0003-2373-769X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "CNIO", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "BU_CNIO", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Provider" ], "note": null } ], "owner": "tdido", "additionDate": "2021-06-14T12:59:22Z", "lastUpdate": "2024-11-24T14:48:24.542882Z", "editPermission": { "type": "group", "authors": [ "sagarcia" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "kmerAnalyzer", "description": "An alignment-free method capable of processing and counting k-mers in a reasonable time, while evaluating multiple values of the k parameter concurrently.", "homepage": "https://github.com/BiodataAnalysisGroup/kmerAnalyzer", "biotoolsID": "kmeranalyzer", "biotoolsCURIE": "biotools:kmeranalyzer", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3472", "term": "k-mer counting" }, { "uri": "http://edamontology.org/operation_3478", "term": "Phylogenetic reconstruction" }, { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_3891", "term": "Essential dynamics" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1667", "term": "E-value" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python", "R" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Greece" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.3389/fgene.2021.618170", "pmid": "34122498", "pmcid": "PMC8194296", "type": [], "version": "1.0", "note": null, "metadata": { "title": "A Computational Framework for Pattern Detection on Unaligned Sequences: An Application on SARS-CoV-2 Data", "abstract": "The exponential growth of genome sequences available has spurred research on pattern detection with the aim of extracting evolutionary signal. Traditional approaches, such as multiple sequence alignment, rely on positional homology in order to reconstruct the phylogenetic history of taxa. Yet, mining information from the plethora of biological data and delineating species on a genetic basis, still proves to be an extremely difficult problem to consider. Multiple algorithms and techniques have been developed in order to approach the problem multidimensionally. Here, we propose a computational framework for identifying potentially meaningful features based on k-mers retrieved from unaligned sequence data. Specifically, we have developed a process which makes use of unsupervised learning techniques in order to identify characteristic k-mers of the input dataset across a range of different k-values and within a reasonable time frame. We use these k-mers as features for clustering the input sequences and identifying differences between the distributions of k-mers across the dataset. The developed algorithm is part of an innovative and much promising approach both to the problem of grouping sequence data based on their inherent characteristic features, as well as for the study of changes in the distributions of k-mers, as the k-value is fluctuating within a range of values. Our framework is fully developed in Python language as an open source software licensed under the MIT License, and is freely available at https://github.com/BiodataAnalysisGroup/kmerAnalyzer.", "date": "2021-05-28T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Pechlivanis N." }, { "name": "Togkousidis A." }, { "name": "Tsagiopoulou M." }, { "name": "Sgardelis S." }, { "name": "Kappas I." }, { "name": "Psomopoulos F." } ], "journal": "Frontiers in Genetics" } } ], "credit": [ { "name": "Fotis E. Psomopoulos", "email": "fpsom@certh.gr", "url": null, "orcidid": "https://orcid.org/0000-0002-0222-4273", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Nikolaos Pechlivanis", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Anastasios Togkousidis", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Ilias Kappas", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "fpsom", "additionDate": "2021-05-17T09:02:15Z", "lastUpdate": "2024-11-24T14:48:06.612968Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "MuGVRE", "description": "The MuG Virtual Research Environment is an analysis platform for 3D/4D genomics analyses. It integrates genomics tools for chromatin dynamics data.", "homepage": "https://www.multiscalegenomics.eu/", "biotoolsID": "mugvre", "biotoolsCURIE": "biotools:mugvre", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "nucleosome_dynamics", "type": "includes" }, { "biotoolsID": "tadbit", "type": "includes" }, { "biotoolsID": "jbrowse", "type": "includes" }, { "biotoolsID": "ngl", "type": "includes" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0292", "term": "Sequence alignment" }, { "uri": "http://edamontology.org/operation_3198", "term": "Read mapping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_3210", "term": "Genome index" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0863", "term": "Sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0475", "term": "Nucleic acid structure prediction" }, { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" }, { "uri": "http://edamontology.org/operation_0279", "term": "Nucleic acid folding analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_2200", "term": "FASTA-like (text)" } ] }, { "data": { "uri": "http://edamontology.org/data_1255", "term": "Sequence features" }, "format": [ { "uri": "http://edamontology.org/format_2305", "term": "GFF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3870", "term": "Trajectory data" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0478", "term": "Molecular docking" }, { "uri": "http://edamontology.org/operation_3900", "term": "DNA-binding protein prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2877", "term": "Protein complex" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3222", "term": "Peak calling" }, { "uri": "http://edamontology.org/operation_1781", "term": "Gene regulatory network analysis" } ], "input": [ { "data": { "uri": 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"term": "Protein interaction data" }, "format": [ { "uri": "http://edamontology.org/format_4002", "term": "pickle" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2478", "term": "Nucleic acid sequence analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1461", "term": "Protein-ligand complex" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2084", "term": "Nucleic acid report" }, "format": [] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2476", "term": "Molecular dynamics" }, { "uri": "http://edamontology.org/operation_2481", "term": "Nucleic acid structure analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0883", "term": "Structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { 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solving cross-linked peptide mass spectra.", "homepage": "https://kojak-ms.systemsbiology.net/", "biotoolsID": "kojak", "biotoolsCURIE": "biotools:kojak", "version": [ "2.0.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" } ], "operatingSystem": [ "Linux", "Windows" ], "language": [ "C++" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [ "Proteomics" ], "link": [], "download": [ { "url": "https://kojak-ms.systemsbiology.net/download.html", "type": "Downloads page", "note": null, "version": "1.0 - 2.0.0" } ], "documentation": [ { "url": 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The Kojak cross-linking software application is a new, efficient approach to identify cross-linked peptides, enabling large-scale analysis of protein-protein interactions by chemical cross-linking techniques. The algorithm integrates spectral processing and scoring schemes adopted from traditional database search algorithms and can identify cross-linked peptides using many different chemical cross-linkers with or without heavy isotope labels. Kojak was used to analyze both novel and existing data sets and was compared to existing cross-linking algorithms. The algorithm provided increased cross-link identifications over existing algorithms and, equally importantly, the results in a fraction of computational time. The Kojak algorithm is open-source, cross-platform, and freely available. This software provides both existing and new cross-linking researchers alike an effective way to derive additional cross-link identifications from new or existing data sets. For new users, it provides a simple analytical resource resulting in more cross-link identifications than other methods.", "date": "2015-05-01T00:00:00Z", "citationCount": 142, "authors": [ { "name": "Hoopmann M.R." }, { "name": "Zelter A." }, { "name": "Johnson R.S." }, { "name": "Riffle M." }, { "name": "Maccoss M.J." }, { "name": "Davis T.N." }, { "name": "Moritz R.L." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1021/acs.jproteome.2c00670", "pmid": "36629399", "pmcid": "PMC10234491", "type": [ "Primary" ], "version": "2.0.0", "note": null, "metadata": { "title": "Improved Analysis of Cross-Linking Mass Spectrometry Data with Kojak 2.0, Advanced by Integration into the Trans-Proteomic Pipeline", "abstract": "Fragmentation ion spectral analysis of chemically cross-linked proteins is an established technology in the proteomics research repertoire for determining protein interactions, spatial orientation, and structure. Here we present Kojak version 2.0, a major update to the original Kojak algorithm, which was developed to identify cross-linked peptides from fragment ion spectra using a database search approach. A substantially improved algorithm with updated scoring metrics, support for cleavable cross-linkers, and identification of cross-links between 15N-labeled homomultimers are among the newest features of Kojak 2.0 presented here. Kojak 2.0 is now integrated into the Trans-Proteomic Pipeline, enabling access to dozens of additional tools within that suite. In particular, the PeptideProphet and iProphet tools for validation of cross-links improve the sensitivity and accuracy of correct cross-link identifications at user-defined thresholds. These new features improve the versatility of the algorithm, enabling its use in a wider range of experimental designs and analysis pipelines. Kojak 2.0 remains open-source and multiplatform.", "date": "2023-02-03T00:00:00Z", "citationCount": 4, "authors": [ { "name": "Hoopmann M.R." }, { "name": "Shteynberg D.D." }, { "name": "Zelter A." }, { "name": "Riffle M." }, { "name": "Lyon A.S." }, { "name": "Agard D.A." }, { "name": "Luan Q." }, { "name": "Nolen B.J." }, { "name": "MacCoss M.J." }, { "name": "Davis T.N." }, { "name": "Moritz R.L." } ], "journal": "Journal of Proteome Research" } } ], "credit": [], "owner": "mhoopmann", "additionDate": "2023-07-26T14:34:25.798022Z", "lastUpdate": "2024-11-24T14:45:40.796568Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Variant Combination Pathogenicity Predictor (VarCoPP) 2.0", "description": "VarCoPP is a machine learning method that predicts the potential pathogenicity of variant combinations in gene pairs. It is based on digenic data present in OLIDA and it was trained against variants from the 1000 Genomes Project. VarCoPP2.0 is a Balanced Random Forest predictor consisting of 400 decision trees. \nA variant combination can be either predicted as disease-causing (i.e. candidate or probably pathogenic) or neutral (i.e. probably neutral). \n\nVarCoPP can be applied for Single Nucleotide Variants (SNVs) and small insertions/deletions from a single individual. It is highly recommended to perform beforehand an initial variant filtering procedure and generally restrict the analysis to variants from up to 150 genes. \n\nVarCoPP was developed in the Interuniversity Institute of Bioinformatics in Brussels, under the collaboration of Université libre de Bruxelles and Vrije Universiteit Brussel.\n\nYou can use it through the online tool ORVAL: https://orval.ibsquare.be.", "homepage": "http://varcopp.ibsquare.be", "biotoolsID": "Variant_Combinaton_Pathogenicity_Predictor", "biotoolsCURIE": "biotools:Variant_Combinaton_Pathogenicity_Predictor", "version": [ "1.0", "2.0" ], "otherID": [], "relation": [ { "biotoolsID": "oligogenic_resource_for_variant_analysis", "type": "includedIn" }, { "biotoolsID": "olida", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2423", "term": "Prediction and recognition" }, { "uri": "http://edamontology.org/operation_3225", "term": "Variant classification" }, { "uri": "http://edamontology.org/operation_3197", "term": "Genetic variation analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Plug-in" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_0634", "term": "Pathology" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "GPL-3.0", "collectionID": [ "ELIXIR-BE", "RD-Connect", "Rare Disease" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Belgium" ], "elixirCommunity": [ "Rare Diseases" ], "link": [ { "url": "https://github.com/oligogenic/VarCoPP2.0", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/sofiapapad90/VarCoPP/", "type": [ "Repository" ], "note": null }, { "url": "https://orval.ibsquare.be", "type": [ "Service" ], "note": "Web app integrating VarCoPP2.0" } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1073/pnas.1815601116", "pmid": "31127050", "pmcid": "PMC6575632", "type": [], "version": "1.0", "note": null, "metadata": { "title": "Predicting disease-causing variant combinations", "abstract": "Notwithstanding important advances in the context of single-variant pathogenicity identification, novel breakthroughs in discerning the origins of many rare diseases require methods able to identify more complex genetic models. We present here the Variant Combinations Pathogenicity Predictor (VarCoPP), a machine-learning approach that identifies pathogenic variant combinations in gene pairs (called digenic or bilocus variant combinations). We show that the results produced by this method are highly accurate and precise, an efficacy that is endorsed when validating the method on recently published independent disease-causing data. Confidence labels of 95% and 99% are identified, representing the probability of a bilocus combination being a true pathogenic result, providing geneticists with rational markers to evaluate the most relevant pathogenic combinations and limit the search space and time. Finally, the VarCoPP has been designed to act as an interpretable method that can provide explanations on why a bilocus combination is predicted as pathogenic and which biological information is important for that prediction. This work provides an important step toward the genetic understanding of rare diseases, paving the way to clinical knowledge and improved patient care.", "date": "2019-06-11T00:00:00Z", "citationCount": 67, "authors": [ { "name": "Papadimitriou S." }, { "name": "Gazzo A." }, { "name": "Versbraegen N." }, { "name": "Nachtegael C." }, { "name": "Aerts J." }, { "name": "Moreau Y." }, { "name": "Van Dooren S." }, { "name": "Nowe A." }, { "name": "Smits G." }, { "name": "Lenaerts T." } ], "journal": "Proceedings of the National Academy of Sciences of the United States of America" } }, { "doi": "10.1186/s12859-023-05291-3", "pmid": "37127601", "pmcid": "PMC10152795", "type": [], "version": "2.0", "note": null, "metadata": { "title": "Faster and more accurate pathogenic combination predictions with VarCoPP2.0", "abstract": "Background: The prediction of potentially pathogenic variant combinations in patients remains a key task in the field of medical genetics for the understanding and detection of oligogenic/multilocus diseases. Models tailored towards such cases can help shorten the gap of missing diagnoses and can aid researchers in dealing with the high complexity of the derived data. The predictor VarCoPP (Variant Combinations Pathogenicity Predictor) that was published in 2019 and identified potentially pathogenic variant combinations in gene pairs (bilocus variant combinations), was the first important step in this direction. Despite its usefulness and applicability, several issues still remained that hindered a better performance, such as its False Positive (FP) rate, the quality of its training set and its complex architecture. Results: We present VarCoPP2.0: the successor of VarCoPP that is a simplified, faster and more accurate predictive model identifying potentially pathogenic bilocus variant combinations. Results from cross-validation and on independent data sets reveal that VarCoPP2.0 has improved in terms of both sensitivity (95% in cross-validation and 98% during testing) and specificity (5% FP rate). At the same time, its running time shows a significant 150-fold decrease due to the selection of a simpler Balanced Random Forest model. Its positive training set now consists of variant combinations that are more confidently linked with evidence of pathogenicity, based on the confidence scores present in OLIDA, the Oligogenic Diseases Database (https://olida.ibsquare.be). The improvement of its performance is also attributed to a more careful selection of up-to-date features identified via an original wrapper method. We show that the combination of different variant and gene pair features together is important for predictions, highlighting the usefulness of integrating biological information at different levels. Conclusions: Through its improved performance and faster execution time, VarCoPP2.0 enables a more accurate analysis of larger data sets linked to oligogenic diseases. Users can access the ORVAL platform (https://orval.ibsquare.be) to apply VarCoPP2.0 on their data.", "date": "2023-12-01T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Versbraegen N." }, { "name": "Gravel B." }, { "name": "Nachtegael C." }, { "name": "Renaux A." }, { "name": "Verkinderen E." }, { "name": "Nowe A." }, { "name": "Lenaerts T." }, { "name": "Papadimitriou S." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Tom Lenaerts", "email": "tlenaert@ulb.ac.be", "url": "http://www.ibsquare.be", "orcidid": "https://orcid.org/0000-0003-3645-1455", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Sofia Papadomitriou", "email": "sofiapapad.bio@gmail.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Interuniversity Institute of Bioinformatics in Brussels", "email": null, "url": "https://ibsquare.be", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "tlenaert@ulb.ac.be", "additionDate": "2019-07-03T15:13:23Z", "lastUpdate": "2024-11-24T14:45:34.041241Z", "editPermission": { "type": "group", "authors": [ "emmaver" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MirGeneDB", "description": "MirGeneDB is a miRBase-derived database for microRNA genes that have been manually validated and annotated. Currently, microRNA genes are available for 75 metazoan species and can be browsed, blasted and downloaded.", "homepage": "http://mirgenedb.org/", "biotoolsID": "mirgen", "biotoolsCURIE": "biotools:mirgen", "version": [ "2.1" ], "otherID": [ { "value": "doi:10.25504/FAIRsharing.QXSgvF", "type": "doi", "version": "2.0" } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_0564", "term": "Sequence visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_1869", "term": "Organism identifier" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3134", "term": "Gene transcript report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] }, { "data": { "uri": "http://edamontology.org/data_0880", "term": "RNA secondary structure" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "Data retrieval: curated miRNA. Organism identifier: a specific miRNA identifier or a species for all miRNAs for that species. Gene transcript report: with metadata and visualization. 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Adhering to uniform and consistent criteria for microRNA annotation and nomenclature, we substantially expanded MirGeneDB with 30 additional species representing previously missing metazoan phyla such as sponges, jellyfish, rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning over ∼800 million years of animal evolution, and contains a total number of 16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new phylogenetically important species, especially those relevant for the study of whole genome duplication events, and through updating evolutionary nodes of origin for many families and genes, we were able to substantially refine our nomenclature system. All changes are traceable in the specifically developed MirGeneDB version tracker. The performance of read-pages is improved and microRNA expression matrices for all tissues and species are now also downloadable. Altogether, this update represents a significant step toward a complete sampling of all major metazoan phyla, and a widely needed foundation for comparative microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.", "date": "2022-01-07T00:00:00Z", "citationCount": 72, "authors": [ { "name": "Fromm B." }, { "name": "Hoye E." }, { "name": "Domanska D." }, { "name": "Zhong X." }, { "name": "Aparicio-Puerta E." }, { "name": "Ovchinnikov V." }, { "name": "Umu S.U." }, { "name": "Chabot P.J." }, { "name": "Kang W." }, { "name": "Aslanzadeh M." }, { "name": "Tarbier M." }, { "name": "Marmol-Sanchez E." }, { "name": "Urgese G." }, { "name": "Johansen M." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Friedlander M.R." }, { "name": "Peterson K.J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkz885", "pmid": "31598695", "pmcid": "PMC6943042", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "MirGeneDB 2.0: The metazoan microRNA complement", "abstract": "Small non-coding RNAs have gained substantial attention due to their roles in animal development and human disorders. Among them, microRNAs are special because individual gene sequences are conserved across the animal kingdom. In addition, unique and mechanistically well understood features can clearly distinguish bona fide miRNAs from the myriad other small RNAs generated by cells. However, making this distinction is not a common practice and, thus, not surprisingly, the heterogeneous quality of available miRNA complements has become a major concern in microRNA research. We addressed this by extensively expanding our curated microRNA gene database-MirGeneDB-to 45 organisms, encompassing a wide phylogenetic swath of animal evolution. By consistently annotating and naming 10,899 microRNA genes in these organisms, we show that previous microRNA annotations contained not only many false positives, but surprisingly lacked >2000 bona fide microRNAs. Indeed, curated microRNA complements of closely related organisms are very similar and can be used to reconstruct ancestral miRNA repertoires. MirGeneDB represents a robust platform for microRNA-based research, providing deeper and more significant insights into the biology and evolution of miRNAs as well as biomedical and biomarker research. MirGeneDB is publicly and freely available at http://mirgenedb.org/.", "date": "2020-01-01T00:00:00Z", "citationCount": 160, "authors": [ { "name": "Fromm B." }, { "name": "Domanska D." }, { "name": "Hoye E." }, { "name": "Ovchinnikov V." }, { "name": "Kang W." }, { "name": "Aparicio-Puerta E." }, { "name": "Johansen M." }, { "name": "Flatmark K." }, { "name": "Mathelier A." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Friedlander M.R." }, { "name": "Peterson K.J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1146/annurev-genet-120213-092023", "pmid": "26473382", "pmcid": "PMC4743252", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "A Uniform System for the Annotation of Vertebrate microRNA Genes and the Evolution of the Human microRNAome", "abstract": "Although microRNAs (miRNAs) are among the most intensively studied molecules of the past 20 years, determining what is and what is not a miRNA has not been straightforward. Here, we present a uniform system for the annotation and nomenclature of miRNA genes. We show that less than a third of the 1,881 human miRBase entries, and only approximately 16% of the 7,095 metazoan miRBase entries, are robustly supported as miRNA genes. Furthermore, we show that the human repertoire of miRNAs has been shaped by periods of intense miRNA innovation and that mature gene products show a very different tempo and mode of sequence evolution than star products. We establish a new open access database-MirGeneDB (http://mirgenedb.org)-to catalog this set of miRNAs, which complements the efforts of miRBase but differs from it by annotating the mature versus star products and by imposing an evolutionary hierarchy upon this curated and consistently named repertoire.", "date": "2015-11-23T00:00:00Z", "citationCount": 412, "authors": [ { "name": "Fromm B." }, { "name": "Billipp T." }, { "name": "Peck L.E." }, { "name": "Johansen M." }, { "name": "Tarver J.E." }, { "name": "King B.L." }, { "name": "Newcomb J.M." }, { "name": "Sempere L.F." }, { "name": "Flatmark K." }, { "name": "Hovig E." }, { "name": "Peterson K.J." } ], "journal": "Annual Review of Genetics" } } ], "credit": [ { "name": "Bastian Fromm", "email": "BastianFromm@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-0352-3037", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer", "Support" ], "note": null }, { "name": "Kevin J. Peterson", "email": "kevin.j.peterson@dartmouth.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer" ], "note": null }, { "name": "The Norwegian Bioinformatics Platform (ELIXIR-Norway) Helpdesk", "email": "support@elixir.no", "url": "https://elixir.no/helpdesk", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Support" ], "note": null }, { "name": "University of Oslo", "email": null, "url": "https://www.uio.no/english/index.html", "orcidid": null, "gridid": "grid.5510.1", "rorid": "01xtthb56", "fundrefid": "10.13039/501100005366", "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "UiO", "additionDate": "2016-02-09T13:19:44Z", "lastUpdate": "2024-11-24T14:45:24.194066Z", "editPermission": { "type": "group", "authors": [ "eca008" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "WEBnma", "description": "WEBnm@ provides quick, automated computation and analysis of low-frequency normal modes for protein structures.", "homepage": "http://apps.cbu.uib.no/webnma", "biotoolsID": "webnma", "biotoolsCURIE": "biotools:webnma", "version": [ "3.5" ], "otherID": [], "relation": [ { "biotoolsID": "numpy", "type": "uses" }, { "biotoolsID": "biopython", "type": "uses" }, { "biotoolsID": "matplotlib", "type": "uses" }, { "biotoolsID": "mustang", "type": "uses" }, { "biotoolsID": "dssp", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0570", "term": "Structure visualisation" }, { "uri": "http://edamontology.org/operation_0244", "term": "Protein flexibility and motion analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_1354", "term": "Sequence profile" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "Constructs elastic network model from alpha carbon coordinates of the protein, and computes properties to describe large scale conformations. Computes normal modes, fluctuation profiles, inter-residue correlations, conformational overlap analysis and vector field representations. Structural amino acid profiles, and normal mode characteristics describing protein motion, visualized in plots and decorated structure visualizations. White space delimited tabular data for normal modes and the provided plots", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2487", "term": "Protein structure comparison" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0886", "term": "Structure alignment" }, "format": [ { "uri": "http://edamontology.org/format_2200", "term": "FASTA-like (text)" } ] }, { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_0889", "term": "Structural profile" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "Performs comparative analysis of the normal modes of protein structures. Computes the Bhattacharyya Coefficient (BC) and the Root Mean Squared Inner Product (RMSIP) of aligned parts of the proteins. Alignment of sets of proteins to be compared. Multiple protein structures Heatmaps, dendrograms and structural amino acid profiles for visual comparison of structural similarity. White space delimited tabular data for the provided plots", "cmd": null } ], "toolType": [ "Web API", "Suite" ], "topic": [ { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0736", "term": "Protein folds and structural domains" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [ "BiB tools", "CBU tools", "UiB tools", "ELIXIR-NO", "ELIXIR-Norway" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Norway" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [ { "url": "https://github.com/reuter-group/webnma3", "type": [ "Repository", "Issue tracker" ], "note": null }, { "url": "https://elixir.no/helpdesk", "type": [ "Helpdesk" ], "note": "Helpdesk and support for ELIXIR Norway services." } ], "download": [], "documentation": [ { "url": "http://apps.cbu.uib.no/webnma3/howto/single", "type": [ "Quick start guide" ], "note": null }, { "url": "http://apps.cbu.uib.no/webnma3/qanda", "type": [ "FAQ" ], "note": null }, { "url": "http://apps.cbu.uib.no/webnma3/about", "type": [ "General", "Citation instructions" ], "note": null } ], "publication": [ { "doi": "10.1186/s12859-014-0427-6", "pmid": "25547242", "pmcid": "PMC4339738", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "WEBnmat v2.0: Web server and services for comparing protein flexibility", "abstract": "Background: Normal mode analysis (NMA) using elastic network models is a reliable and cost-effective computational method to characterise protein flexibility and by extension, their dynamics. Further insight into the dynamics-function relationship can be gained by comparing protein motions between protein homologs and functional classifications. This can be achieved by comparing normal modes obtained from sets of evolutionary related proteins. Results: We have developed an automated tool for comparative NMA of a set of pre-aligned protein structures. The user can submit a sequence alignment in the FASTA format and the corresponding coordinate files in the Protein Data Bank (PDB) format. The computed normalised squared atomic fluctuations and atomic deformation energies of the submitted structures can be easily compared on graphs provided by the web user interface. The web server provides pairwise comparison of the dynamics of all proteins included in the submitted set using two measures: the Root Mean Squared Inner Product and the Bhattacharyya Coefficient. The Comparative Analysis has been implemented on our web server for NMA, WEBnmat, which also provides recently upgraded functionality for NMA of single protein structures. This includes new visualisations of protein motion, visualisation of inter-residue correlations and the analysis of conformational change using the. In addition, programmatic access to WEBnmat is now available through a SOAP-based web service. WEBnmat is available at. Conclusion: WEBnmat v2.0 is an online tool offering unique capability for comparative NMA on multiple protein structures. Along with a convenient web interface, powerful computing resources, and several methods for mode analyses, WEBnmat facilitates the assessment of protein flexibility within protein families and superfamilies. These analyses can give a good view of how the structures move and how the flexibility is conserved over the different structures.", "date": "2014-12-30T00:00:00Z", "citationCount": 87, "authors": [ { "name": "Tiwari S.P." }, { "name": "Fuglebakk E." }, { "name": "Hollup S.M." }, { "name": "Skjaerven L." }, { "name": "Cragnolini T." }, { "name": "Grindhaug S.H." }, { "name": "Tekle K.M." }, { "name": "Reuter N." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1186/1471-2105-6-52", "pmid": "15762993", "pmcid": "PMC1274249", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "WEBnm@: A web application for normal mode analyses of proteins", "abstract": "Background: Normal mode analysis (NMA) has become the method of choice to investigate the slowest motions in macromolecular systems. NMA is especially useful for large biomolecular assemblies, such as transmembrane channels or virus capsids. NMA relies on the hypothesis that the vibrational normal modes having the lowest frequencies (also named soft modes) describe the largest movements in a protein and are the ones that are functionally relevant. Results: We developed a web-based server to perform normal modes calculations and different types of analyses. Starting from a structure file provided by the user in the PDB format, the server calculates the normal modes and subsequently offers the user a series of automated calculations; normalized squared atomic displacements, vector field representation and animation of the first six vibrational modes. Each analysis is performed independently from the others and results can be visualized using only a web browser. No additional plug-in or software is required. For users who would like to analyze the results with their favorite software, raw results can also be downloaded. The application is available on http://www.bioinfo.no/tools/normalmodes. We present here the underlying theory, the application architecture and an illustration of its features using a large transmembrane protein as an example. Conclusion: We built an efficient and modular web application for normal mode analysis of proteins. Non specialists can easily and rapidly evaluate the degree of flexibility of multi-domain protein assemblies and characterize the large amplitude movements of their domains. © 2005 Hollup et al; licensee BioMed Central Ltd.", "date": "2005-03-11T00:00:00Z", "citationCount": 105, "authors": [ { "name": "Hollup S.M." }, { "name": "Salensminde G." }, { "name": "Reuter N." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Nathalie Reuter", "email": "Nathalie.Reuter@uib.no", "url": "http://www.cbu.uib.no/reuter/", "orcidid": "https://orcid.org/0000-0002-3649-7675", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer" ], "note": null }, { "name": "Sandhya P Tiwari", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-0747-3826", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Kidane M Tekle", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Tristan Cragnolini", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Svenn H Grindhaug", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Lars Skjærven", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Gisle Salensminde", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Edvin Fuglebakk", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Siv M Hollup", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Department of Molecular Biology, University of Bergen, Norway", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Computational Biology Unit, Department of Informatics, University of Bergen, Norway", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "UiB", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "UiB", "additionDate": "2016-03-17T13:51:10Z", "lastUpdate": "2024-11-24T14:44:59.665860Z", "editPermission": { "type": "group", "authors": [ "eca008" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Planet Microbe", "description": "Enabling the discovery and integration of oceanographic ‘omics, environmental and physiochemical data layers.", "homepage": "https://www.planetmicrobe.org/", "biotoolsID": "planet_microbe", "biotoolsCURIE": "biotools:planet_microbe", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2403", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/operation_0291", "term": "Sequence clustering" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_0361", "term": "Sequence annotation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Bioinformatics portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3387", "term": "Marine biology" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" } ], "operatingSystem": [ "Linux" ], "language": [ "Elm" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/hurwitzlab/planet-microbe-app", "type": [ "Repository" ], "note": "Planet Microbe Application" }, { "url": "https://github.com/hurwitzlab/planet-microbe-datapackages", "type": [ "Repository" ], "note": "Planet Microbe frictionless data packages" }, { "url": "https://github.com/hurwitzlab/planet-microbe-ontology", "type": [ "Repository" ], "note": "Planet Microbe ontology" }, { "url": "https://github.com/hurwitzlab/planet-microbe-functional-annotation", "type": [ "Repository" ], "note": "Functional Annotation Pipeline" }, { "url": "https://github.com/hurwitzlab/planet-microbe-semantic-web-analysis", "type": [ "Repository" ], "note": "Semantic web analysis" } ], "download": [ { "url": "https://github.com/hurwitzlab/planet-microbe-app", "type": "Source code", "note": "Source code for the website", "version": "1.0" } ], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkaa637", "pmid": "32735679", "pmcid": "PMC7778950", "type": [ "Primary" ], "version": "1.0", "note": "In recent years, large-scale oceanic sequencing efforts have provided a deeper understanding of marine microbial communities and their dynamics. These research endeavors require the acquisition of complex and varied datasets through large, interdisciplinary and collaborative efforts. However, no unifying framework currently exists for the marine science community to integrate sequencing data with physical, geological, and geochemical datasets. Planet Microbe is a web-based platform that enables data discovery from curated historical and on-going oceanographic sequencing efforts. In Planet Microbe, each 'omics sample is linked with other biological and physiochemical measurements collected for the same water samples or during the same sample collection event, to provide a broader environmental context. This work highlights the need for curated aggregation efforts that can enable new insights into high-quality metagenomic datasets.", "metadata": { "title": "Planet Microbe: A platform for marine microbiology to discover and analyze interconnected 'omics and environmental data'", "abstract": "In recent years, large-scale oceanic sequencing efforts have provided a deeper understanding of marine microbial communities and their dynamics. These research endeavors require the acquisition of complex and varied datasets through large, interdisciplinary and collaborative efforts. However, no unifying framework currently exists for the marine science community to integrate sequencing data with physical, geological, and geochemical datasets. Planet Microbe is a web-based platform that enables data discovery from curated historical and ongoing oceanographic sequencing efforts. In Planet Microbe, each 'omics sample is linked with other biological and physiochemical measurements collected for the same water samples or during the same sample collection event, to provide a broader environmental context. This work highlights the need for curated aggregation efforts that can enable new insights into high-quality metagenomic datasets. Planet Microbe is freely accessible from https://www.planetmicrobe.org/.", "date": "2021-01-08T00:00:00Z", "citationCount": 13, "authors": [ { "name": "Ponsero A.J." }, { "name": "Bomhoff M." }, { "name": "Blumberg K." }, { "name": "Youens-Clark K." }, { "name": "Herz N.M." }, { "name": "Wood-Charlson E.M." }, { "name": "Delong E.F." }, { "name": "Hurwitz B.L." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Bonnie Hurwitz", "email": "bhurwitz@arizona.edu", "url": "http://www.hurwitzlab.org/", "orcidid": "https://orcid.org/0000-0001-8699-957X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "Professor at the University of Arizona known for her work in cyberinfrastructure development." }, { "name": "Alise Ponsero", "email": "aponsero@arizona.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-4125-7561", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Kai Blumberg", "email": "kblumberg@arizona.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-3410-4655", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Matthew Miller", "email": "mattmiller899@arizona.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-3491-8763", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Matthew Bomhoff", "email": "mbomhoff@arizona.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-8014-9184", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Ken Youens-Clark", "email": "kyclark@arizona.edu", "url": null, "orcidid": "https://orcid.org/0000-0001-9961-144X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "bhurwitz", "additionDate": "2023-09-26T23:26:58.411470Z", "lastUpdate": "2024-11-24T14:39:10.273022Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Planet Microbe", "description": "Enabling the discovery and integration of oceanographic ‘omics, environmental and physiochemical data layers.", "homepage": "https://www.planetmicrobe.org/", "biotoolsID": "planetmicrobe", "biotoolsCURIE": "biotools:planetmicrobe", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2403", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/operation_0291", "term": "Sequence clustering" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_0361", "term": "Sequence annotation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Bioinformatics portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3387", "term": "Marine biology" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" } ], "operatingSystem": [ "Linux" ], "language": [ "Elm" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/hurwitzlab/planet-microbe-app", "type": [ "Repository" ], "note": "Planet Microbe Application" }, { "url": "https://github.com/hurwitzlab/planet-microbe-datapackages", "type": [ "Repository" ], "note": "Planet Microbe frictionless data packages" }, { "url": "https://github.com/hurwitzlab/planet-microbe-ontology", "type": [ "Repository" ], "note": "Planet Microbe ontology" }, { "url": "https://github.com/hurwitzlab/planet-microbe-functional-annotation", "type": [ "Repository" ], "note": "Functional Annotation Pipeline" }, { "url": "https://github.com/hurwitzlab/planet-microbe-semantic-web-analysis", "type": [ "Repository" ], "note": "Semantic web analysis" } ], "download": [ { "url": "https://github.com/hurwitzlab/planet-microbe-app", "type": "Source code", "note": "Source code for the website", "version": "1.0" } ], "documentation": [ { "url": "https://hurwitzlab.gitbook.io/planet-microbe-documentation/", "type": [ "General" ], "note": "Documentation on how to use the website" } ], "publication": [ { "doi": "10.1093/nar/gkaa637", "pmid": "32735679", "pmcid": "PMC7778950", "type": [ "Primary" ], "version": "1.0", "note": "In recent years, large-scale oceanic sequencing efforts have provided a deeper understanding of marine microbial communities and their dynamics. These research endeavors require the acquisition of complex and varied datasets through large, interdisciplinary and collaborative efforts. However, no unifying framework currently exists for the marine science community to integrate sequencing data with physical, geological, and geochemical datasets. Planet Microbe is a web-based platform that enables data discovery from curated historical and on-going oceanographic sequencing efforts. In Planet Microbe, each 'omics sample is linked with other biological and physiochemical measurements collected for the same water samples or during the same sample collection event, to provide a broader environmental context. This work highlights the need for curated aggregation efforts that can enable new insights into high-quality metagenomic datasets.", "metadata": { "title": "Planet Microbe: A platform for marine microbiology to discover and analyze interconnected 'omics and environmental data'", "abstract": "In recent years, large-scale oceanic sequencing efforts have provided a deeper understanding of marine microbial communities and their dynamics. These research endeavors require the acquisition of complex and varied datasets through large, interdisciplinary and collaborative efforts. However, no unifying framework currently exists for the marine science community to integrate sequencing data with physical, geological, and geochemical datasets. Planet Microbe is a web-based platform that enables data discovery from curated historical and ongoing oceanographic sequencing efforts. In Planet Microbe, each 'omics sample is linked with other biological and physiochemical measurements collected for the same water samples or during the same sample collection event, to provide a broader environmental context. This work highlights the need for curated aggregation efforts that can enable new insights into high-quality metagenomic datasets. Planet Microbe is freely accessible from https://www.planetmicrobe.org/.", "date": "2021-01-08T00:00:00Z", "citationCount": 13, "authors": [ { "name": "Ponsero A.J." }, { "name": "Bomhoff M." }, { "name": "Blumberg K." }, { "name": "Youens-Clark K." }, { "name": "Herz N.M." }, { "name": "Wood-Charlson E.M." }, { "name": "Delong E.F." }, { "name": "Hurwitz B.L." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Bonnie Hurwitz", "email": "bhurwitz@arizona.edu", "url": "http://www.hurwitzlab.org/", "orcidid": "https://orcid.org/0000-0001-8699-957X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "Professor at the University of Arizona known for her work in cyberinfrastructure development." }, { "name": "Alise Ponsero", "email": "aponsero@arizona.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-4125-7561", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Kai Blumberg", "email": "kblumberg@arizona.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-3410-4655", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Matthew Miller", "email": "mattmiller899@arizona.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-3491-8763", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Matthew Bomhoff", "email": "mbomhoff@arizona.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-8014-9184", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Ken Youens-Clark", "email": "kyclark@arizona.edu", "url": null, "orcidid": "https://orcid.org/0000-0001-9961-144X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "bhurwitz", "additionDate": "2023-09-26T23:32:38.521840Z", "lastUpdate": "2024-11-24T14:39:08.746037Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "lineagespot", "description": "Lineagespot is a framework written in R, and aims to identify and assign different SARS-CoV-2 lineages based on a single variant file (i.e., variant calling format).", "homepage": "https://github.com/BiodataAnalysisGroup/lineagespot", "biotoolsID": "lineagespot", "biotoolsCURIE": "biotools:lineagespot", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3227", "term": "Variant calling" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" }, { "uri": "http://edamontology.org/topic_3299", "term": "Evolutionary biology" }, { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "MIT", "collectionID": [ "COVID-19" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Greece" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1038/s41598-022-06625-6", "pmid": "35177697", "pmcid": "PMC8854625", "type": [], "version": "1.0", "note": null, "metadata": { "title": "Detecting SARS-CoV-2 lineages and mutational load in municipal wastewater and a use-case in the metropolitan area of Thessaloniki, Greece", "abstract": "The COVID-19 pandemic represents an unprecedented global crisis necessitating novel approaches for, amongst others, early detection of emerging variants relating to the evolution and spread of the virus. Recently, the detection of SARS-CoV-2 RNA in wastewater has emerged as a useful tool to monitor the prevalence of the virus in the community. Here, we propose a novel methodology, called lineagespot, for the monitoring of mutations and the detection of SARS-CoV-2 lineages in wastewater samples using next-generation sequencing (NGS). Our proposed method was tested and evaluated using NGS data produced by the sequencing of 14 wastewater samples from the municipality of Thessaloniki, Greece, covering a 6-month period. The results showed the presence of SARS-CoV-2 variants in wastewater data. lineagespot was able to record the evolution and rapid domination of the Alpha variant (B.1.1.7) in the community, and allowed the correlation between the mutations evident through our approach and the mutations observed in patients from the same area and time periods. lineagespot is an open-source tool, implemented in R, and is freely available on GitHub and registered on bio.tools.", "date": "2022-12-01T00:00:00Z", "citationCount": 19, "authors": [ { "name": "Pechlivanis N." }, { "name": "Tsagiopoulou M." }, { "name": "Maniou M.C." }, { "name": "Togkousidis A." }, { "name": "Mouchtaropoulou E." }, { "name": "Chassalevris T." }, { "name": "Chaintoutis S.C." }, { "name": "Petala M." }, { "name": "Kostoglou M." }, { "name": "Karapantsios T." }, { "name": "Laidou S." }, { "name": "Vlachonikola E." }, { "name": "Chatzidimitriou A." }, { "name": "Papadopoulos A." }, { "name": "Papaioannou N." }, { "name": "Dovas C.I." }, { "name": "Argiriou A." }, { "name": "Psomopoulos F." } ], "journal": "Scientific Reports" } } ], "credit": [ { "name": "Fotis E. Psomopoulos", "email": "fpsom@certh.gr", "url": null, "orcidid": "https://orcid.org/0000-0002-0222-4273", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Nikolaos Pechlivanis,", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-2502-612X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Maria Tsagiopoulou", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-1653-0327", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "fpsom", "additionDate": "2021-05-17T08:32:18Z", "lastUpdate": "2024-11-24T14:34:44.476503Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-CZ" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "MaCPepDB - Mass Centric Peptide Database", "description": "A Database to Quickly Access All Tryptic Peptides of the UniProtKB", "homepage": "https://macpepdb.mpc.rub.de/", "biotoolsID": "macpepdb_-_mass_centric_peptide_database", "biotoolsCURIE": "biotools:macpepdb_-_mass_centric_peptide_database", "version": [ "2.3.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [], "language": [ "Python", "JavaScript", "SQL" ], "license": null, "collectionID": [ "CUBiMed.RUB", "BioInfra.Prot" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/mpc-bioinformatics/macpepdb", "type": [ "Repository" ], "note": "Backend implementation written in Flask" }, { "url": "https://github.com/mpc-bioinformatics/macpepdb", "type": [ "Repository" ], "note": "Frontend implementation written in NuxtJS" } ], "download": [], "documentation": [ { "url": "https://macpepdb.mpc.rub.de/docs/api", "type": [ "API documentation" ], "note": null }, { "url": "https://github.com/mpc-bioinformatics/macpepdb/blob/main/Readme.md", "type": [ "Installation instructions" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jproteome.0c00967", "pmid": "33724838", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "MaCPepDB: A Database to Quickly Access All Tryptic Peptides of the UniProtKB", "abstract": "Protein sequence databases play a crucial role in the majority of the currently applied mass-spectrometry-based proteomics workflows. Here UniProtKB serves as one of the major sources, as it combines the information of several smaller databases and enriches the entries with additional biological information. For the identification of peptides in a sample by tandem mass spectra, as generated by data-dependent acquisition, protein sequence databases provide the basis for most spectrum identification search engines. In addition, for targeted proteomics approaches like selected reaction monitoring (SRM) and parallel reaction monitoring (PRM), knowledge of the peptide sequences, their masses, and whether they are unique for a protein is essential. Because most bottom-up proteomics approaches use trypsin to cleave the proteins in a sample, the tryptic peptides contained in a protein database are of great interest. We present a database, called MaCPepDB (mass-centric peptide database), that consists of the complete tryptic digest of the Swiss-Prot and TrEMBL parts of UniProtKB. This database is especially designed to not only allow queries of peptide sequences and return the respective information about connected proteins and thus whether a peptide is unique but also allow queries of specific masses of peptides or precursors of MS/MS spectra. Furthermore, posttranslational modifications can be considered in a query as well as different mass deviations for posttranslational modifications. Hence the database can be used by a sequence query not only to, for example, check in which proteins of the UniProt database a tryptic peptide can be found but also to find possibly interfering peptides in PRM/SRM experiments using the mass query. The complete database contains currently 5 939 244 990 peptides from 185 561 610 proteins (UniProt version 2020_03), for which a single query usually takes less than 1 s. For easy exploration of the data, a web interface was developed. A REST application programming interface (API) for programmatic and workflow access is also available at https://macpepdb.mpc.rub.de.", "date": "2021-04-02T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Uszkoreit J." }, { "name": "Winkelhardt D." }, { "name": "Barkovits K." }, { "name": "Wulf M." }, { "name": "Roocke S." }, { "name": "Marcus K." }, { "name": "Eisenacher M." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Julian Uszkoreit", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0001-7522-4007", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Dirk Winkelhardt", "email": "dirk.winkelhardt@rub.de", "url": null, "orcidid": "https://orcid.org/0000-0001-8770-2221", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "PD Dr. Martin Eisenacher", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-2687-7444", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "di_hardt", "additionDate": "2023-07-25T12:35:27.605861Z", "lastUpdate": "2024-11-24T14:30:53.360087Z", "editPermission": { "type": "group", "authors": [ "di_hardt", "julianu", "BioInfra.Prot" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Meta-SNP", "description": "Meta-predictor of disease causing variants.", "homepage": "http://snps.biofold.org/meta-snp", "biotoolsID": "meta-snp", "biotoolsCURIE": "biotools:meta-snp", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3225", "term": "Variant classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_2209", "term": "Mutation ID" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1622", "term": "Disease report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_0123", "term": "Protein properties" }, { "uri": "http://edamontology.org/topic_0634", "term": "Pathology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://snps.biofold.org/meta-snp/pages/help.html", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1186/1471-2164-14-s3-s2", "pmid": "23819846", "pmcid": "PMC3839641", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "A highly accurate heuristic algorithm for the haplotype assembly problem.", "abstract": "Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation in human DNA. The sequence of SNPs in each of the two copies of a given chromosome in a diploid organism is referred to as a haplotype. Haplotype information has many applications such as gene disease diagnoses, drug design, etc. The haplotype assembly problem is defined as follows: Given a set of fragments sequenced from the two copies of a chromosome of a single individual, and their locations in the chromosome, which can be pre-determined by aligning the fragments to a reference DNA sequence, the goal here is to reconstruct two haplotypes (h1, h2) from the input fragments. Existing algorithms do not work well when the error rate of fragments is high. Here we design an algorithm that can give accurate solutions, even if the error rate of fragments is high. We first give a dynamic programming algorithm that can give exact solutions to the haplotype assembly problem. The time complexity of the algorithm is O(n × 2t × t), where n is the number of SNPs, and t is the maximum coverage of a SNP site. The algorithm is slow when t is large. To solve the problem when t is large, we further propose a heuristic algorithm on the basis of the dynamic programming algorithm. Experiments show that our heuristic algorithm can give very accurate solutions. We have tested our algorithm on a set of benchmark datasets. Experiments show that our algorithm can give very accurate solutions. It outperforms most of the existing programs when the error rate of the input fragments is high.", "date": "2013-01-01T00:00:00Z", "citationCount": 27, "authors": [ { "name": "Deng F." }, { "name": "Cui W." }, { "name": "Wang L." } ], "journal": "BMC genomics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "http://www.biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Support" ], "note": null }, { "name": "Emidio Capriotti", "email": "emidio.capriotti@gmail.com", "url": null, "orcidid": "http://orcid.org/0000-0002-2323-0963", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2017-03-01T14:15:32Z", "lastUpdate": "2024-11-24T14:11:28.058280Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-ITA-BOLOGNA", "emidio" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DeepSig", "description": "Prediction of secretory signal peptides in protein sequences", "homepage": "https://busca.biocomp.unibo.it/deepsig/", "biotoolsID": "deepsig", "biotoolsCURIE": "biotools:deepsig", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0418", "term": "Protein signal peptide detection" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_3510", "term": "Protein sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0123", "term": "Protein properties" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "GPL-3.0", "collectionID": [ "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/BolognaBiocomp/deepsig", "type": "Source code", "note": null, "version": "1.2.5" }, { "url": "https://hub.docker.com/r/bolognabiocomp/deepsig", "type": "Container file", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/BolognaBiocomp/deepsig", "type": [ "Command-line options" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btx818", "pmid": "29280997", "pmcid": "PMC5946842", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "DeepSig: Deep learning improves signal peptide detection in proteins", "abstract": "Motivation The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Results Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. Availability and implementation DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website.", "date": "2018-05-15T00:00:00Z", "citationCount": 85, "authors": [ { "name": "Savojardo C." }, { "name": "Martelli P.L." }, { "name": "Fariselli P." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "http://biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact" ], "note": null }, { "name": "Pier Luigi Martelli", "email": "pierluigi.martelli@unibo.it", "url": "http://biocomp.unibo.it", "orcidid": "https://orcid.org/0000-0002-0274-5669", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2018-05-28T14:50:09Z", "lastUpdate": "2024-11-24T14:07:51.469245Z", "editPermission": { "type": "group", "authors": [ "savo", "ELIXIR-ITA-BOLOGNA" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "plantRNA", "description": "The PlantRNA database compiles tRNA gene sequences retrieved from fully annotated nuclear, plastidial and mitochondrial genomes of photosynthetic organisms.", "homepage": "http://plantrna.ibmp.cnrs.fr/", "biotoolsID": "plantrna", "biotoolsCURIE": "biotools:plantrna", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" } ], "operatingSystem": [], "language": [], "license": "CC-BY-SA-4.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1111/tpj.15997", "pmid": "36196656", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "PlantRNA 2.0: an updated database dedicated to tRNAs of photosynthetic eukaryotes", "abstract": "PlantRNA (http://plantrna.ibmp.cnrs.fr/) is a comprehensive database of transfer RNA (tRNA) gene sequences retrieved from fully annotated nuclear, plastidial and mitochondrial genomes of photosynthetic organisms. In the first release (PlantRNA 1.0), tRNA genes from 11 organisms were annotated. In this second version, the annotation was implemented to 51 photosynthetic species covering the whole phylogenetic tree of photosynthetic organisms, from the most basal group of Archeplastida, the glaucophyte Cyanophora paradoxa, to various land plants. tRNA genes from lower photosynthetic organisms such as streptophyte algae or lycophytes as well as extremophile photosynthetic species such as Eutrema parvulum were incorporated in the database. As a whole, about 37 000 tRNA genes were accurately annotated. In the frame of the tRNA genes annotation from the genome of the Rhodophyte Chondrus crispus, non-canonical splicing sites in the D- or T-regions of tRNA molecules were identified and experimentally validated. As for PlantRNA 1.0, comprehensive biological information including 5′- and 3′-flanking sequences, A and B box sequences, region of transcription initiation and poly(T) transcription termination stretches, tRNA intron sequences and tRNA mitochondrial import are included.", "date": "2022-11-01T00:00:00Z", "citationCount": 9, "authors": [ { "name": "Cognat V." }, { "name": "Pawlak G." }, { "name": "Pflieger D." }, { "name": "Drouard L." } ], "journal": "Plant Journal" } }, { "doi": "10.1093/nar/gks935", "pmid": "23066098", "pmcid": "PMC3531208", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "PlantRNA, a database for tRNAs of photosynthetic eukaryotes", "abstract": "PlantRNA database (http://plantrna.ibmp.cnrs.fr/) compiles transfer RNA (tRNA) gene sequences retrieved from fully annotated plant nuclear, plastidial and mitochondrial genomes. The set of annotated tRNA gene sequences has been manually curated for maximum quality and confidence. The novelty of this database resides in the inclusion of biological information relevant to the function of all the tRNAs entered in the library. This includes 5′- and 3′-flanking sequences, A and B box sequences, region of transcription initiation and poly(T) transcription termination stretches, tRNA intron sequences, aminoacyl-tRNA synthetases and enzymes responsible for tRNA maturation and modification. Finally, data on mitochondrial import of nuclear-encoded tRNAs as well as the bibliome for the respective tRNAs and tRNA-binding proteins are also included. The current annotation concerns complete genomes from 11 organisms: five flowering plants (Arabidopsis thaliana, Oryza sativa, Populus trichocarpa, Medicago truncatula and Brachypodium distachyon), a moss (Physcomitrella patens), two green algae (Chlamydomonas rein-hardtii and Ostreococcus tauri), one glaucophyte (Cyanophora paradoxa), one brown alga (Ectocarpus siliculosus) and a pennate diatom (Phaeodactylum tricornutum). The database will be regularly updated and implemented with new plant genome annotations so as to provide extensive information on tRNA biology to the research community. © The Author(s) 2012.", "date": "2013-01-01T00:00:00Z", "citationCount": 55, "authors": [ { "name": "Cognat V." }, { "name": "Pawlak G." }, { "name": "Duchene A.-M." }, { "name": "Daujat M." }, { "name": "Gigant A." }, { "name": "Salinas T." }, { "name": "Michaud M." }, { "name": "Gutmann B." }, { "name": "Giege P." }, { "name": "Gobert A." }, { "name": "Marechal-Drouard L." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Valerie Cognat", "email": "valerie.cognat@cnrs.fr", "url": null, "orcidid": "https://orcid.org/0000-0001-9337-2767", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "vcognat", "additionDate": "2024-06-13T14:41:01.342264Z", "lastUpdate": "2024-11-24T13:55:20.404756Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "MetaPathways", "description": "MetaPathways is a meta’omic analysis pipeline for the annotation and analysis for environmental sequence information. MetaPathways include metagenomic or metatranscriptomic sequence data. The pipeline consists of four operational stages including: Quality Control, Feature Prediction, Functional Annotation, Pathway Inference.", "homepage": "https://metapathways.readthedocs.io/en/dev/index.html", "biotoolsID": "metapathways", "biotoolsCURIE": "biotools:metapathways", "version": [ "3.5" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3672", "term": "Gene functional annotation" }, { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3779", "term": "Annotated text" }, "format": [ { "uri": "http://edamontology.org/format_3751", "term": "DSV" } ] } ], "note": "Use MetaPathways to annotate a metagenome.", "cmd": "metapathways run \\\n -i $[input_metagenome.fa] \\\n -d ${path/to/save/reference_databases} \\\n -o ${path/to/output} \\\n -t ${threads}" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" }, { "uri": "http://edamontology.org/topic_3796", "term": "Population genomics" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "MPL-2.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://metapathways.readthedocs.io/en/dev/index.html", "type": [ "Other" ], "note": null } ], "download": [ { "url": "https://anaconda.org/Hallamlab/metapathways", "type": "Tool wrapper (Other)", "note": null, "version": "3.5" }, { "url": "https://quay.io/repository/hallamlab/metapathways", "type": "Container file", "note": null, "version": "3.5" }, { "url": "https://bitbucket.org/BCB2/metapathways/src/dev/", "type": "Source code", "note": null, "version": "3.5" } ], "documentation": [ { "url": "https://metapathways.readthedocs.io/en/dev/index.html", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1101/2024.06.04.597460", "pmid": null, "pmcid": null, "type": [], "version": "1.0", "note": null, "metadata": null }, { "doi": "10.1093/bioinformatics/btv361", "pmid": "26076725", "pmcid": "PMC4595896", "type": [], "version": "2.5", "note": null, "metadata": { "title": "MetaPathways v2.5: Quantitative functional, taxonomic and usability improvements", "abstract": "Next-generation sequencing is producing vast amounts of sequence information from natural and engineered ecosystems. Although this data deluge has an enormous potential to transform our lives, knowledge creation and translation need software applications that scale with increasing data processing and analysis requirements. Here, we present improvements to MetaPathways, an annotation and analysis pipeline for environmental sequence information that expedites this transformation. We specifically address pathway prediction hazards through integration of a weighted taxonomic distance and enable quantitative comparison of assembled annotations through a normalized read-mapping measure. Additionally, we improve LAST homology searches through BLAST-equivalent E-values and output formats that are natively compatible with prevailing software applications. Finally, an updated graphical user interface allows for keyword annotation query and projection onto user-defined functional gene hierarchies, including the Carbohydrate-Active Enzyme database.", "date": "2015-03-25T00:00:00Z", "citationCount": 40, "authors": [ { "name": "Konwar K.M." }, { "name": "Hanson N.W." }, { "name": "Bhatia M.P." }, { "name": "Kim D." }, { "name": "Wu S.-J." }, { "name": "Hahn A.S." }, { "name": "Morgan-Lang C." }, { "name": "Cheung H.K." }, { "name": "Hallam S.J." } ], "journal": "Bioinformatics" } }, { "doi": "10.1186/1471-2105-14-202", "pmid": "23800136", "pmcid": "PMC3695837", "type": [], "version": "1.0", "note": null, "metadata": { "title": "MetaPathways: A modular pipeline for constructing pathway/genome databases from environmental sequence information", "abstract": "Background: A central challenge to understanding the ecological and biogeochemical roles of microorganisms in natural and human engineered ecosystems is the reconstruction of metabolic interaction networks from environmental sequence information. The dominant paradigm in metabolic reconstruction is to assign functional annotations using BLAST. Functional annotations are then projected onto symbolic representations of metabolism in the form of KEGG pathways or SEED subsystems.Results: Here we present MetaPathways, an open source pipeline for pathway inference that uses the PathoLogic algorithm to map functional annotations onto the MetaCyc collection of reactions and pathways, and construct environmental Pathway/Genome Databases (ePGDBs) compatible with the editing and navigation features of Pathway Tools. The pipeline accepts assembled or unassembled nucleotide sequences, performs quality assessment and control, predicts and annotates noncoding genes and open reading frames, and produces inputs to PathoLogic. In addition to constructing ePGDBs, MetaPathways uses MLTreeMap to build phylogenetic trees for selected taxonomic anchor and functional gene markers, converts General Feature Format (GFF) files into concatenated GenBank files for ePGDB construction based on third-party annotations, and generates useful file formats including Sequin files for direct GenBank submission and gene feature tables summarizing annotations, MLTreeMap trees, and ePGDB pathway coverage summaries for statistical comparisons.Conclusions: MetaPathways provides users with a modular annotation and analysis pipeline for predicting metabolic interaction networks from environmental sequence information using an alternative to KEGG pathways and SEED subsystems mapping. It is extensible to genomic and transcriptomic datasets from a wide range of sequencing platforms, and generates useful data products for microbial community structure and function analysis. The MetaPathways software package, installation instructions, and example data can be obtained from http://hallam.microbiology.ubc.ca/MetaPathways. © 2013 Konwar et al.; licensee BioMed Central Ltd.", "date": "2013-06-21T00:00:00Z", "citationCount": 82, "authors": [ { "name": "Konwar K.M." }, { "name": "Hanson N.W." }, { "name": "Page A.P." }, { "name": "Hallam S.J." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": null, "email": "shallam@mail.ubc.ca", "url": "https://hallam.microbiology.ubc.ca/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "mbs_import", "additionDate": "2017-08-03T18:51:07Z", "lastUpdate": "2024-11-24T13:47:09.737653Z", "editPermission": { "type": "group", "authors": [ "mclaughlinr2" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "REDItools", "description": "Python scripts to detect RNA editing in deep transcriptome sequencing data (RNAseq)", "homepage": "https://github.com/BioinfoUNIBA/REDItools", "biotoolsID": "reditools", "biotoolsCURIE": "biotools:reditools", "version": [ "1.3", "2.0" ], "otherID": [ { "value": "RRID:SCR_012133", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2945", "term": "Analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1916", "term": "Alignment" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2526", "term": "Text data" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "Run REDItools on RNA sequences", "cmd": "REDItoolDnaRna.py -i rnaseq.bam -f myreference.fa -o myoutputfolder" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Python" ], "license": "MIT", "collectionID": [ "ELIXIR-ITA-CNR" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/BioinfoUNIBA/REDItools", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btt287", "pmid": "23742983", "pmcid": null, "type": [ "Primary" ], "version": "1.0-1.3", "note": null, "metadata": { "title": "REDItools: High-throughput RNA editing detection made easy", "abstract": "The reliable detection of RNA editing sites from massive sequencing data remains challenging and, although several methodologies have been proposed, no computational tools have been released to date. Here, we introduce REDItools a suite of python scripts to perform high-throughput investigation of RNA editing using next-generation sequencing data.Availability and implementation: REDItools are in python programming language and freely available at http://code.google. com/p/reditools/.Contact: or graziano.pesole@uniba.itSupplementary information: Supplementary data are available at Bioinformatics online. © 2013 The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.", "date": "2013-07-15T00:00:00Z", "citationCount": 201, "authors": [ { "name": "Picardi E." }, { "name": "Pesole G." } ], "journal": "Bioinformatics" } }, { "doi": "10.1186/s12859-020-03562-x", "pmid": "32838738", "pmcid": "PMC7446188", "type": [], "version": "2.0", "note": null, "metadata": { "title": "HPC-REDItools: A novel HPC-aware tool for improved large scale RNA-editing analysis", "abstract": "Background: RNA editing is a widespread co-/post-transcriptional mechanism that alters primary RNA sequences through the modification of specific nucleotides and it can increase both the transcriptome and proteome diversity. The automatic detection of RNA-editing from RNA-seq data is computational intensive and limited to small data sets, thus preventing a reliable genome-wide characterisation of such process. Results: In this work we introduce HPC-REDItools, an upgraded tool for accurate RNA-editing events discovery from large dataset repositories. Availability: https://github.com/BioinfoUNIBA/REDItools2. Conclusions: HPC-REDItools is dramatically faster than the previous version, REDItools, enabling big-data analysis by means of a MPI-based implementation and scaling almost linearly with the number of available cores.", "date": "2020-08-21T00:00:00Z", "citationCount": 21, "authors": [ { "name": "Flati T." }, { "name": "Gioiosa S." }, { "name": "Spallanzani N." }, { "name": "Tagliaferri I." }, { "name": "Diroma M.A." }, { "name": "Pesole G." }, { "name": "Chillemi G." }, { "name": "Picardi E." }, { "name": "Castrignano T." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1038/s41596-019-0279-7", "pmid": "31996844", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Investigating RNA editing in deep transcriptome datasets with REDItools and REDIportal", "abstract": "RNA editing is a widespread post-transcriptional mechanism able to modify transcripts through insertions/deletions or base substitutions. It is prominent in mammals, in which millions of adenosines are deaminated to inosines by members of the ADAR family of enzymes. A-to-I RNA editing has a plethora of biological functions, but its detection in large-scale transcriptome datasets is still an unsolved computational task. To this aim, we developed REDItools, the first software package devoted to the RNA editing profiling in RNA-sequencing (RNAseq) data. It has been successfully used in human transcriptomes, proving the tissue and cell type specificity of RNA editing as well as its pervasive nature. Outcomes from large-scale REDItools analyses on human RNAseq data have been collected in our specialized REDIportal database, containing more than 4.5 million events. Here we describe in detail two bioinformatic procedures based on our computational resources, REDItools and REDIportal. In the first procedure, we outline a workflow to detect RNA editing in the human cell line NA12878, for which transcriptome and whole genome data are available. In the second procedure, we show how to identify dysregulated editing at specific recoding sites in post-mortem brain samples of Huntington disease donors. On a 64-bit computer running Linux with ≥32 GB of random-access memory (RAM), both procedures should take ~76 h, using 4 to 24 cores. Our protocols have been designed to investigate RNA editing in different organisms with available transcriptomic and/or genomic reads. Scripts to complete both procedures and a docker image are available at https://github.com/BioinfoUNIBA/REDItools.", "date": "2020-03-01T00:00:00Z", "citationCount": 69, "authors": [ { "name": "Lo Giudice C." }, { "name": "Tangaro M.A." }, { "name": "Pesole G." }, { "name": "Picardi E." } ], "journal": "Nature Protocols" } }, { "doi": "10.1007/978-1-0716-1307-8_14", "pmid": "33835447", "pmcid": null, "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "RNA Editing Detection in HPC Infrastructures", "abstract": "RNA editing by A-to-I deamination is a relevant co/posttranscriptional modification carried out by ADAR enzymes. In humans, it has pivotal cellular effects and its deregulation has been linked to a variety of human disorders including neurological and neurodegenerative diseases and cancer. Despite its biological relevance, the detection of RNA editing variants in large transcriptome sequencing experiments (RNAseq) is yet a challenging computational task. To drastically reduce computing times we have developed a novel REDItools version able to identify A-to-I events in huge amount of RNAseq data employing High Performance Computing (HPC) infrastructures. Here we show how to use REDItools v2 in HPC systems.", "date": "2021-01-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Giudice C.L." }, { "name": "Mansi L." }, { "name": "Flati T." }, { "name": "Gioiosa S." }, { "name": "Chillemi G." }, { "name": "Libro P." }, { "name": "Castrignano T." }, { "name": "Pesole G." }, { "name": "Picardi E." } ], "journal": "Methods in Molecular Biology" } }, { "doi": "10.1002/0471250953.bi1212s49", "pmid": "25754992", "pmcid": null, "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "Using REDItools to detect RNA editing events in NGS datasets", "abstract": "RNAediting is a post-transcriptional/co-transcriptional molecular phenomenon whereby a genetic message is modified from the corresponding DNA template by means of substitutions, insertions, and/or deletions. It occurs in a variety of organisms and different cellular locations through evolutionally and biochemically unrelated proteins. RNA editing has a plethora of biological effects including the modulation of alternative splicing and fine-tuning of gene expression. RNA editing events by base substitutions can be detected on a genomic scale by NGS technologies through the REDItools package, an ad hoc suite of Python scripts to study RNA editing using RNA-Seq and DNA-Seq data or RNA-Seq data alone. REDItools implement effective filters to minimize biases due to sequencing errors, mapping errors, and SNPs. The package is freely available at Google Code repository (http://code.google.com/p/reditools/) and released under the MIT license. In the present unit we show three basic protocols corresponding to three main REDItools scripts.", "date": "2015-01-01T00:00:00Z", "citationCount": 25, "authors": [ { "name": "Picardi E." }, { "name": "D'Erchia A.M." }, { "name": "A. Antonio" }, { "name": "G. Graziano" } ], "journal": "Current Protocols in Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-CNR", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-6549-0114", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Ernesto Picardi", "email": "ernesto.picardi@uniba.it", "url": "https://www.uniba.it/docenti/picardi-ernesto/en", "orcidid": "https://orcid.org/0000-0002-6549-0114", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-CNR", "additionDate": "2015-02-05T13:24:16Z", "lastUpdate": "2024-02-09T14:59:52.330758Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-ITA-BARI" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Mass Dynamics", "description": "A software platform for analysis and visualization of label-free and tandem mass tag (TMT) data-dependent acquisition (DDA) bottom-up proteomics data, including pathway and gene set enrichment analyses.", "homepage": "https://massdynamics.com/", "biotoolsID": "mass_dynamics", "biotoolsCURIE": "biotools:mass_dynamics", "version": [ "1.0", "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2945", "term": "Analysis" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1021/acs.jproteome.1c00683", "pmid": "34647461", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Mass Dynamics 1.0: A Streamlined, Web-Based Environment for Analyzing, Sharing, and Integrating Label-Free Data", "abstract": "Label-free quantification (LFQ) of shotgun proteomics data is a popular and robust method for the characterization of relative protein abundance between samples. Many analytical pipelines exist for the automation of this analysis, and some tools exist for the subsequent representation and inspection of the results of these pipelines. Mass Dynamics 1.0 (MD 1.0) is a web-based analysis environment that can analyze and visualize LFQ data produced by software such as MaxQuant. Unlike other tools, MD 1.0 utilizes a cloud-based architecture to enable researchers to store their data, enabling researchers to not only automatically process and visualize their LFQ data but also annotate and share their findings with collaborators and, if chosen, to easily publish results to the community. With a view toward increased reproducibility and standardization in proteomics data analysis and streamlining collaboration between researchers, MD 1.0 requires minimal parameter choices and automatically generates quality control reports to verify experiment integrity. Here, we demonstrate that MD 1.0 provides reliable results for protein expression quantification, emulating Perseus on benchmark datasets over a wide dynamic range. The MD 1.0 platform is available globally via: https://app.massdynamics.com/.", "date": "2021-11-05T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Bloom J." }, { "name": "Triantafyllidis A." }, { "name": "Quaglieri A." }, { "name": "Burton Ngov P." }, { "name": "Infusini G." }, { "name": "Webb A." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1101/2022.12.12.517480", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": null } ], "credit": [], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2024-01-18T10:05:20.317333Z", "lastUpdate": "2024-01-18T12:57:09.002286Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "seqfu", "description": "A collection of utilities to manipulate FASTA and FASTQ files, supporting Gzipped input.", "homepage": "https://telatin.github.io/seqfu2/", "biotoolsID": "seqfu", "biotoolsCURIE": "biotools:seqfu", "version": [ "1.10.0", "1.11.0", "1.12.0", "1.13.0", "1.14.0", "1.15.0", "1.16.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3695", "term": "Filtering" }, { "uri": "http://edamontology.org/operation_3187", "term": "Sequence contamination filtering" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_2545", "term": "FASTQ-like format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_2545", "term": "FASTQ-like format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0077", "term": "Nucleic acids" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://telatin.github.io/seqfu2", "type": [ "Other" ], "note": "Documentation" }, { "url": "https://github.com/telatin/seqfu2/", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/telatin/seqfu2", "type": "Software package", "note": null, "version": null }, { "url": "https://github.com/telatin/seqfu2/releases", "type": "Downloads page", "note": null, "version": null } ], "documentation": [ { "url": "https://telatin.github.io/seqfu2/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.3390/bioengineering8050059", "pmid": "34066939", "pmcid": "PMC8148589", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Seqfu: A suite of utilities for the robust and reproducible manipulation of sequence files", "abstract": "© 2021 by the authors. Licensee MDPI, Basel, Switzerland.Sequence files formats (FASTA and FASTQ) are commonly used in bioinformatics, molecular biology and biochemistry. With the advent of next-generation sequencing (NGS) technologies, the number of FASTQ datasets produced and analyzed has grown exponentially, urging the development of dedicated software to handle, parse, and manipulate such files efficiently. Several bioinformatics packages are available to filter and manipulate FASTA and FASTQ files, yet some essential tasks remain poorly supported, leaving gaps that any workflow analysis of NGS datasets must fill with custom scripts. This can introduce harmful variability and performance bottlenecks in pivotal steps. Here we present a suite of tools, called SeqFu (Sequence Fastx utilities), that provides a broad range of commands to perform both common and specialist operations with ease and is designed to be easily implemented in high-performance analytical pipelines. SeqFu includes high-performance implementation of algorithms to interleave and deinterleave FASTQ files, merge Illumina lanes, and perform various quality controls (identification of degenerate primers, analysis of length statistics, extraction of portions of the datasets). SeqFu dereplicates sequences from multiple files keeping track of their provenance. SeqFu is developed in Nim for high-performance processing, is freely available, and can be installed with the popular package manager Miniconda.", "date": "2021-01-01T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Telatin A." }, { "name": "Fariselli P." }, { "name": "Birolo G." } ], "journal": "Bioengineering" } } ], "credit": [], "owner": "telatin", "additionDate": "2020-03-17T13:50:50Z", "lastUpdate": "2022-10-03T11:16:44.940017Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MISTIC", "description": "MISTIC (MISsense deleTeriousness predICtor), a prediction tool to reveal disease-relevant deleterious missense variants based on an original combination of two complementary machine learning algorithms using a soft voting system that integrates 113 missense features, ranging from multi-ethnic minor allele frequencies and evolutionary conservation, to physiochemical and biochemical properties of amino acids.", "homepage": "http://lbgi.fr/mistic", "biotoolsID": "mistic_predictor", "biotoolsCURIE": "biotools:mistic_predictor", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3225", "term": "Variant classification" }, { "uri": "http://edamontology.org/operation_3226", "term": "Variant prioritisation" }, { "uri": "http://edamontology.org/operation_0331", "term": "Variant effect prediction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web API", "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" }, { "uri": "http://edamontology.org/topic_3676", "term": "Exome sequencing" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [ "Python" ], "license": "MIT", "collectionID": [ "Rare Disease" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "France" ], "elixirCommunity": [ "Rare Diseases" ], "link": [], "download": [ { "url": "http://lbgi.fr/mistic/download", "type": "Downloads page", "note": null, "version": "1.0" }, { "url": "https://lbgi.fr/api/index.rvt?api=mistic", "type": "API specification", "note": null, "version": "1.0" } ], "documentation": [], "publication": [ { "doi": "10.1371/journal.pone.0236962", "pmid": "32735577", "pmcid": "PMC7394404", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "MISTIC: A prediction tool to reveal disease-relevant deleterious missense variants", "abstract": "Copyright: © 2020 Chennen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.The diffusion of next-generation sequencing technologies has revolutionized research and diagnosis in the field of rare Mendelian disorders, notably via whole-exome sequencing (WES). However, one of the main issues hampering achievement of a diagnosis via WES analyses is the extended list of variants of unknown significance (VUS), mostly composed of missense variants. Hence, improved solutions are needed to address the challenges of identifying potentially deleterious variants and ranking them in a prioritized short list. We present MISTIC (MISsense deleTeriousness predICtor), a new prediction tool based on an original combination of two complementary machine learning algorithms using a soft voting system that integrates 113 missense features, ranging from multi-ethnic minor allele frequencies and evolutionary conservation, to physiochemical and biochemical properties of amino acids. Our approach also uses training sets with a wide spectrum of variant profiles, including both high-confidence positive (deleterious) and negative (benign) variants. Compared to recent state-of-the-art prediction tools in various benchmark tests and independent evaluation scenarios, MISTIC exhibits the best and most consistent performance, notably with the highest AUC value (> 0.95). Importantly, MISTIC maintains its high performance in the specific case of discriminating deleterious variants from benign variants that are rare or population-specific. In a clinical context, MISTIC drastically reduces the list of VUS (<30%) and significantly improves the ranking of “causative” deleterious variants. Pre-computed MISTIC scores for all possible human missense variants are available at http://lbgi.fr/mistic.", "date": "2020-07-01T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Chennen K." }, { "name": "Weber T." }, { "name": "Lornage X." }, { "name": "Kress A." }, { "name": "Bohm J." }, { "name": "Thompson J." }, { "name": "Laporte J." }, { "name": "Poch O." } ], "journal": "PLoS ONE" } } ], "credit": [ { "name": "Kirsley Chennen", "email": "kchennen@unistra.fr", "url": null, "orcidid": "https://orcid.org/0000-0001-9268-6748", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "Thomas Weber", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-0807-6363", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Olivier Poch", "email": "olivier.poch@unistra.fr", "url": null, "orcidid": "https://orcid.org/0000-0002-7134-3217", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Contributor" ], "note": null } ], "owner": "kchennen", "additionDate": "2022-03-24T09:57:50.414985Z", "lastUpdate": "2022-03-24T13:12:19.605062Z", "editPermission": { "type": "private", "authors": [ "kchennen" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "EDAM-Browser", "description": "The EDAM Browser is a client-side web-based visualization javascript widget of the EDAM ontology. \nThe EDAM Browser provides users a simple and performant interface to explore EDAM when annotating or searching for bioinformatics resources.\nIts goals are to help describing bio-related resources and service with EDAM, and to facilitate and foster community contributions to EDAM.", "homepage": "https://github.com/IFB-ElixirFr/edam-browser", "biotoolsID": "edam-browser", "biotoolsCURIE": "biotools:edam-browser", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3559", "term": "Ontology visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0582", "term": "Ontology" }, "format": [ { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Plug-in", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0605", "term": "Informatics" }, { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Interoperability" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/IFB-ElixirFr/edam-browser", "type": [ "Repository" ], "note": null }, { "url": "https://ifb-elixirfr.github.io/edam-browser/", "type": [ "Service" ], "note": null }, { "url": "https://github.com/IFB-ElixirFr/edam-browser/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://ifb-elixirfr.github.io/edam-browser/demo.html", "type": [ "Training material" ], "note": "A demo on how to use it; Tutorial" }, { "url": "https://github.com/IFB-ElixirFr/edam-browser/blob/master/paper_resources/long_paper_version.md", "type": [ "Other" ], "note": null } ], "publication": [ { "doi": "10.21105/joss.00698", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": null } ], "credit": [ { "name": "Bryan Brancotte", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-8669-5525", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null }, { "name": "Hervé Ménager", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-7552-1009", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Maintainer" ], "note": null }, { "name": "Christophe Blanchet", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "Hager Eldakroury", "email": null, "url": "https://github.com/HagerDakroury", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null } ], "owner": "BryanBrancotte", "additionDate": "2019-01-22T09:41:33Z", "lastUpdate": "2022-01-03T15:45:09.883379Z", "editPermission": { "type": "group", "authors": [ "hmenager", "hmenager@asu.edu" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "VarGenius", "description": "VarGenius is a platform for analysis of variants from DNA sequencing data. Currently it can be used for WES and Panels. Starting from fastq files it can execute the GATK Best Practices pipeline doing both single calling and joint calling. Then it executes Annovar for variant annotation and generates a readable output in tabular and XLS format. All the data extracted from the samples (variants, genotypes, etc..) are uploaded into a Postgres database which can be used for further downstream analyses.", "homepage": "https://github.com/frankMusacchia/VarGenius", "biotoolsID": "VarGenius", "biotoolsCURIE": "biotools:VarGenius", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "vargenius-hzd", "type": "includes" } ], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_2533", "term": "DNA mutation" } ], "operatingSystem": [ "Linux" ], "language": [ "R", "Perl" ], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [ { "url": "https://groups.google.com/forum/#!forum/VarGenius", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://github.com/frankMusacchia/VarGenius", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://github.com/frankMusacchia/VarGenius/tree/master/GUIDE", "type": [ "Installation instructions" ], "note": null } ], "publication": [ { "doi": "10.1186/s12859-018-2532-4", "pmid": "30541431", "pmcid": "PMC6291943", "type": [ "Primary", "Benchmarking study" ], "version": "1.0", "note": null, "metadata": { "title": "VarGenius executes cohort-level DNA-seq variant calling and annotation and allows to manage the resulting data through a PostgreSQL database", "abstract": "© 2018 The Author(s).Background: Targeted resequencing has become the most used and cost-effective approach for identifying causative mutations of Mendelian diseases both for diagnostics and research purposes. Due to very rapid technological progress, NGS laboratories are expanding their capabilities to address the increasing number of analyses. Several open source tools are available to build a generic variant calling pipeline, but a tool able to simultaneously execute multiple analyses, organize, and categorize the samples is still missing. Results: Here we describe VarGenius, a Linux based command line software able to execute customizable pipelines for the analysis of multiple targeted resequencing data using parallel computing. VarGenius provides a database to store the output of the analysis (calling quality statistics, variant annotations, internal allelic variant frequencies) and sample information (personal data, genotypes, phenotypes). VarGenius can also perform the \"joint analysis\" of hundreds of samples with a single command, drastically reducing the time for the configuration and execution of the analysis. VarGenius executes the standard pipeline of the Genome Analysis Tool-Kit (GATK) best practices (GBP) for germinal variant calling, annotates the variants using Annovar, and generates a user-friendly output displaying the results through a web page. VarGenius has been tested on a parallel computing cluster with 52 machines with 120GB of RAM each. Under this configuration, a 50 M whole exome sequencing (WES) analysis for a family was executed in about 7h (trio or quartet); a joint analysis of 30 WES in about 24 h and the parallel analysis of 34 single samples from a 1 M panel in about 2 h. Conclusions: We developed VarGenius, a \"master\" tool that faces the increasing demand of heterogeneous NGS analyses and allows maximum flexibility for downstream analyses. It paves the way to a different kind of analysis, centered on cohorts rather than on singleton. Patient and variant information are stored into the database and any output file can be accessed programmatically. VarGenius can be used for routine analyses by biomedical researchers with basic Linux skills providing additional flexibility for computational biologists to develop their own algorithms for the comparison and analysis of data. The software is freely available at: https://github.com/frankMusacchia/VarGenius", "date": "2018-12-12T00:00:00Z", "citationCount": 8, "authors": [ { "name": "Musacchia F." }, { "name": "Ciolfi A." }, { "name": "Mutarelli M." }, { "name": "Bruselles A." }, { "name": "Castello R." }, { "name": "Pinelli M." }, { "name": "Basu S." }, { "name": "Banfi S." }, { "name": "Casari G." }, { "name": "Tartaglia M." }, { "name": "Nigro V." }, { "name": "Torella A." }, { "name": "Esposito G." }, { "name": "Cappuccio G." }, { "name": "Mancano G." }, { "name": "Maitz S." }, { "name": "Brunetti-Pierri N." }, { "name": "Parenti G." }, { "name": "Selicorni A." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-TELETHON", "email": "f.musacchia@tigem.it", "url": null, "orcidid": "https://orcid.org/0000-0001-9440-1080", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "FrankMusacchia", "additionDate": "2019-02-14T08:17:30Z", "lastUpdate": "2021-10-08T08:49:21.521364Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "metaQuantome", "description": "metaQuantome software suite analyzes the state of a microbiome by leveraging complex taxonomic and functional hierarchies to summarize peptide-level quantitative information. metaQuantome offers differential abundance analysis, principal components analysis, and clustered heat map visualizations, as well as exploratory analysis for a single sample or experimental condition.", "homepage": "https://github.com/galaxyproteomics/metaquantome", "biotoolsID": "metaQuantome", "biotoolsCURIE": "biotools:metaQuantome", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2939", "term": "Principal component visualisation" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_3459", "term": "Functional clustering" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" }, { "uri": "http://edamontology.org/operation_3741", "term": "Differential protein expression analysis" }, { "uri": "http://edamontology.org/operation_0531", "term": "Heat map generation" }, { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" }, { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" }, { "uri": "http://edamontology.org/operation_3695", "term": "Filtering" }, { "uri": "http://edamontology.org/operation_3658", "term": "Statistical inference" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0945", "term": "Peptide identification" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_1872", "term": "Taxonomic classification" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_2583", "term": "GO concept ID (molecular function)" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_1011", "term": "EC number" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2583", "term": "GO concept ID (molecular function)" }, "format": [ { "uri": "http://edamontology.org/format_3547", "term": "Image format" } ] }, { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3547", "term": "Image format" } ] }, { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3547", "term": "Image format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Suite" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3941", "term": "Metatranscriptomics" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1074/mcp.RA118.001240", "pmid": "31235611", "pmcid": "PMC6692774", "type": [ "Method" ], "version": "1.0", "note": "https://www.mcponline.org/content/18/8_suppl_1/S82", "metadata": { "title": "MetaQuantome: An integrated, quantitative metaproteomics approach reveals connections between taxonomy and protein function in complex microbiomes", "abstract": "© 2019 Easterly et al.Microbiome research offers promising insights into the impact of microorganisms on biological systems. Metaproteomics, the study of microbial proteins at the community level, integrates genomic, transcriptomic, and proteomic data to determine the taxonomic and functional state of a microbiome. However, standard metaproteomics software is subject to several limitations, commonly supporting only spectral counts, emphasizing exploratory analysis rather than hypothesis testing and rarely offering the ability to analyze the interaction of function and taxonomy - that is, which taxa are responsible for different processes. Here we present metaQuantome, a novel, multifaceted software suite that analyzes the state of a microbiome by leveraging complex taxonomic and functional hierarchies to summarize peptide-level quantitative information, emphasizing label-free intensity-based methods. For experiments with multiple experimental conditions, metaQuantome offers differential abundance analysis, principal components analysis, and clustered heat map visualizations, as well as exploratory analysis for a single sample or experimental condition. We benchmark meta- Quantome analysis against standard methods, using two previously published datasets: (1) an artificially assembled microbial community dataset (taxonomy benchmarking) and (2) a dataset with a range of recombinant human proteins spiked into an Escherichia coli background (functional benchmarking). Furthermore, we demonstrate the use of metaQuantome on a previously published human oral microbiome dataset. In both the taxonomic and functional benchmarking analyses, metaQuantome quantified taxonomic and functional terms more accurately than standard summarization- based methods. We use the oral microbiome dataset to demonstrate metaQuantome's ability to produce publication- quality figures and elucidate biological processes of the oral microbiome. metaQuantome enables advanced investigation of metaproteomic datasets, which should be broadly applicable to microbiome-related research. In the interest of accessible, flexible, and reproducible analysis, metaQuantome is open source and available on the command line and in Galaxy.", "date": "2019-01-01T00:00:00Z", "citationCount": 11, "authors": [ { "name": "Easterly C.W." }, { "name": "Sajulga R." }, { "name": "Mehta S." }, { "name": "Johnson J." }, { "name": "Kumar P." }, { "name": "Hubler S." }, { "name": "Mesuere B." }, { "name": "Rudney J." }, { "name": "Griffin T.J." }, { "name": "Jagtap P.D." } ], "journal": "Molecular and Cellular Proteomics" } }, { "doi": "10.1021/ACS.JPROTEOME.0C00960", "pmid": "33683127", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Updates on metaQuantome Software for Quantitative Metaproteomics", "abstract": "© 2021 American Chemical Society.metaQuantome is a software suite that enables the quantitative analysis, statistical evaluation. and visualization of mass-spectrometry-based metaproteomics data. In the latest update of this software, we have provided several extensions, including a step-by-step training guide, the ability to perform statistical analysis on samples from multiple conditions, and a comparative analysis of metatranscriptomics data. The training module, accessed via the Galaxy Training Network, will help users to use the suite effectively both for functional as well as for taxonomic analysis. We extend the ability of metaQuantome to now perform multi-data-point quantitative and statistical analyses so that studies with measurements across multiple conditions, such as time-course studies, can be analyzed. With an eye on the multiomics analysis of microbial communities, we have also initiated the use of metaQuantome statistical and visualization tools on outputs from metatranscriptomics data, which complements the metagenomic and metaproteomic analyses already available. For this, we have developed a tool named MT2MQ (\"metatranscriptomics to metaQuantome\"), which takes in outputs from the ASaiM metatranscriptomics workflow and transforms them so that the data can be used as an input for comparative statistical analysis and visualization via metaQuantome. We believe that these improvements to metaQuantome will facilitate the use of the software for quantitative metaproteomics and metatranscriptomics and will enable multipoint data analysis. These improvements will take us a step toward integrative multiomic microbiome analysis so as to understand dynamic taxonomic and functional responses of these complex systems in a variety of biological contexts. The updated metaQuantome and MT2MQ are open-source software and are available via the Galaxy Toolshed and GitHub.", "date": "2021-04-02T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Mehta S." }, { "name": "Kumar P." }, { "name": "Crane M." }, { "name": "Johnson J.E." }, { "name": "Sajulga R." }, { "name": "Nguyen D.D.A." }, { "name": "McGowan T." }, { "name": "Arntzen M." }, { "name": "Griffin T.J." }, { "name": "Jagtap P.D." } ], "journal": "Journal of Proteome Research" } } ], "credit": [], "owner": "pjagtap", "additionDate": "2020-03-10T11:06:45Z", "lastUpdate": "2021-05-27T07:59:11Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "ARADEEPOPSIS", "description": "ARADEEPOPSIS is a software tool that enables plant researchers to non-invasively score plant growth, biomass accumulation and senescence from image data in a highly parallelized, high throughput, yet easy to use manner.", "homepage": "https://github.com/Gregor-Mendel-Institute/aradeepopsis", "biotoolsID": "aradeepopsis", "biotoolsCURIE": "biotools:aradeepopsis", "version": [ "1.3", "1.2.1", "1.2", "1.1", "1.0", "1.3.1" ], "otherID": [ { "value": "doi:10.5281/zenodo.3946320", "type": "doi", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" }, { "uri": "http://edamontology.org/operation_3443", "term": "Image analysis" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2428", "term": "Validation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3603", "term": "PNG" }, { "uri": "http://edamontology.org/format_3579", "term": "JPG" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] }, { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_3382", "term": "Imaging" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" }, { "uri": "http://edamontology.org/topic_3298", "term": "Phenomics" } ], "operatingSystem": [], "language": [ "Python", "R", "Groovy" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Gregor-Mendel-Institute/aradeepopsis", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://quay.io/beckerlab/aradeepopsis-base", "type": "Container file", "note": null, "version": "1.3" }, { "url": "https://quay.io/beckerlab/aradeepopsis-shiny", "type": "Container file", "note": null, "version": "1.3" }, { "url": "https://zenodo.org/record/3946618", "type": "Downloads page", "note": "Trained models", "version": null }, { "url": "https://zenodo.org/record/3946393", "type": "Downloads page", "note": "Training data", "version": null } ], "documentation": [ { "url": "https://github.com/Gregor-Mendel-Institute/aradeepopsis#readme", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1105/tpc.20.00318", "pmid": "33037149", "pmcid": "PMC7721323", "type": [], "version": "1.2.1", "note": null, "metadata": { "title": "ARADEEPOPSIS, an automated workflow for top-view plant phenomics using semantic segmentation of leaf States", "abstract": "© 2020 The authors.Linking plant phenotype to genotype is a common goal to both plant breeders and geneticists. However, collecting phenotypic data for large numbers of plants remain a bottleneck. Plant phenotyping is mostly image based and therefore requires rapid and robust extraction of phenotypic measurements from image data. However, because segmentation tools usually rely on color information, they are sensitive to background or plant color deviations. We have developed a versatile, fully open-source pipeline to extract phenotypic measurements from plant images in an unsupervised manner. ARADEEPOPSIS (https://github.com/Gregor-Mendel-Institute/aradeepopsis) uses semantic segmentation of top-view images to classify leaf tissue into three categories: healthy, anthocyanin rich, and senescent. This makes it particularly powerful at quantitative phenotyping of different developmental stages, mutants with aberrant leaf color and/or phenotype, and plants growing in stressful conditions. On a panel of 210 natural Arabidopsis (Arabidopsis thaliana) accessions, we were able to not only accurately segment images of phenotypically diverse genotypes but also to identify known loci related to anthocyanin production and early necrosis in genome-wide association analyses. Our pipeline accurately processed images of diverse origin, quality, and background composition, and of a distantly related Brassicaceae. ARADEEPOPSIS is deployable on most operating systems and high-performance computing environments and can be used independently of bioinformatics expertise and resources.", "date": "2020-12-01T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Huther P." }, { "name": "Schandry N." }, { "name": "Jandrasits K." }, { "name": "Bezrukov I." }, { "name": "Becker C." } ], "journal": "Plant Cell" } }, { "doi": "10.1101/2020.04.01.018192", "pmid": null, "pmcid": null, "type": [], "version": "1.0", "note": null, "metadata": null } ], "credit": [ { "name": "Patrick Hüther", "email": "patrick.huether@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-3315-2484", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null }, { "name": "Claude Becker", "email": "claude.becker@gmi.oeaw.ac.at", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "phue", "additionDate": "2021-01-18T08:40:04Z", "lastUpdate": "2021-05-18T08:11:06Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PICKLE", "description": "PICKLE (Protein InteraCtion KnowLedgebasE) is a meta-database for the direct protein-protein interactome of the human and the mouse proteomes, integrating publicly available source protein-protein interaction (PPI) databases via genetic information ontology. PICKLE integrates the primary PPI datasets by superimposing them on the UniProtKB/Swiss-Prot reviewed complete proteome of the human (RHCP) and the mouse (RMCP) ontology network without any a priori transformations.", "homepage": "http://www.pickle.gr", "biotoolsID": "pickle", "biotoolsCURIE": "biotools:pickle", "version": [ "3.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0276", "term": "Protein interaction network analysis" }, { "uri": "http://edamontology.org/operation_3802", "term": "Sorting" }, { "uri": "http://edamontology.org/operation_3695", "term": "Filtering" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" }, { "uri": "http://edamontology.org/operation_3083", "term": "Pathway or network visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1009", "term": "Protein name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1025", "term": "Gene identifier" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_2338", "term": "Ontology identifier" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" }, { "uri": "http://edamontology.org/topic_2815", "term": "Human biology" }, { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_3574", "term": "Human genetics" }, { "uri": "http://edamontology.org/topic_3396", "term": "Systems medicine" } ], "operatingSystem": [ "Windows" ], "language": [ "C#" ], "license": null, "collectionID": [], "maturity": "Emerging", "cost": null, "accessibility": "Open access", "elixirPlatform": [ "Data" ], "elixirNode": [ "Greece" ], "elixirCommunity": [], "link": [ { "url": "http://www.pickle.gr", "type": [ "Other" ], "note": "Content available to any user with no restrictions\nCopyright: University of Patras & FORTH/ICE-HT, Greece" } ], "download": [ { "url": "http://www.pickle.gr/Downloads", "type": "Biological data", "note": "The current and archived PICKLE PPI datasets at the UniProt and gene levels can be freely downloaded from the PICKLE webpage.", "version": "active and archived versions" }, { "url": "http://www.pickle.gr/Downloads", "type": "Biological data", "note": "The current and archived PICKLE genetic information ontology networks are available in owl format.", "version": "active and archived versions" } ], "documentation": [ { "url": "http://www.pickle.gr", "type": [ "General" ], "note": "The web portal of the meta-database" } ], "publication": [ { "doi": "10.1186/1752-0509-7-96", "pmid": "24088582", "pmcid": "PMC5638325", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Reconstruction of the experimentally supported human protein interactome: What can we learn?", "abstract": "Background: Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. Results: First, we defined the UniProtKB manually reviewed human \" complete\" proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Conclusions: Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human \" complete\" proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms. © 2013 Klapa et al.; licensee BioMed Central Ltd.", "date": "2013-10-02T00:00:00Z", "citationCount": 15, "authors": [ { "name": "Klapa M.I." }, { "name": "Tsafou K." }, { "name": "Theodoridis E." }, { "name": "Tsakalidis A." }, { "name": "Moschonas N.K." } ], "journal": "BMC Systems Biology" } }, { "doi": "10.1371/journal.pone.0186039", "pmid": "29023571", "pmcid": null, "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "PICKLE 2.0: A human protein-protein interaction meta-database employing data integration via genetic information ontology", "abstract": "© 2017 Gioutlakis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.It has been acknowledged that source databases recording experimentally supported human protein-protein interactions (PPIs) exhibit limited overlap. Thus, the reconstruction of a comprehensive PPI network requires appropriate integration of multiple heterogeneous primary datasets, presenting the PPIs at various genetic reference levels. Existing PPI meta-databases perform integration via normalization; namely, PPIs are merged after converted to a certain target level. Hence, the node set of the integrated network depends each time on the number and type of the combined datasets. Moreover, the irreversible a priori normalization process hinders the identification of normalization artifacts in the integrated network, which originate from the nonlinearity characterizing the genetic information flow. PICKLE (Protein InteraCtion KnowLedgebasE) 2.0 implements a new architecture for this recently introduced human PPI meta-database. Its main novel feature over the existing meta-databases is its approach to primary PPI dataset integration via genetic information ontology. Building upon the PICKLE principles of using the reviewed human complete proteome (RHCP) of UniProtKB/Swiss-Prot as the reference protein interactor set, and filtering out protein interactions with low probability of being direct based on the available evidence, PICKLE 2.0 first assembles the RHCP genetic information ontology network by connecting the corresponding genes, nucleotide sequences (mRNAs) and proteins (UniProt entries) and then integrates PPI datasets by superimposing them on the ontology network without any a priori transformations. Importantly, this process allows the resulting heterogeneous integrated network to be reversibly normalized to any level of genetic reference without loss of the original information, the latter being used for identification of normalization biases, and enables the appraisal of potential false positive interactions through PPI source database cross-checking. The PICKLE web-based interface (www.pickle.gr) allows for the simultaneous query of multiple entities and provides integrated human PPI networks at either the protein (UniProt) or the gene level, at three PPI filtering modes.", "date": "2017-10-01T00:00:00Z", "citationCount": 20, "authors": [ { "name": "Gioutlakis A." }, { "name": "Klapa M.I." }, { "name": "Moschonas N.K." } ], "journal": "PLoS ONE" } }, { "doi": "10.13140/RG.2.2.16985.21608", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": "Poster Presentation in the ELIXIR All Hands Meeting", "metadata": null }, { "doi": "10.1093/bioinformatics/btaa1070", "pmid": "33367505", "pmcid": "PMC8034533", "type": [ "Method" ], "version": "3.0", "note": "The PICKLE 3.0 upgrade refers to the enrichment of this human protein–protein interaction (PPI) meta-database with the mouse protein interactome.", "metadata": null } ], "credit": [ { "name": "Nicholas Moschonas", "email": "n_moschonas@med.upatras.gr", "url": "http://www.pickle.gr", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Maria Klapa", "email": "mklapa@iceht.forth.gr", "url": "http://www.iceht.forth.gr/staff/klapa.html", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "mklapa", "additionDate": "2017-09-11T10:43:38Z", "lastUpdate": "2021-05-17T08:54:15Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "rPredictorDB", "description": "A web database for prediction, analysis and storage of secondary structures of RNAs.", "homepage": "http://rpredictordb.elixir-czech.cz", "biotoolsID": "rpredictor", "biotoolsCURIE": "biotools:rpredictor", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "traveler", "type": "uses" 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"http://edamontology.org/format_3604", "term": "SVG" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "Predict secondary structure for own sequences using templates in the database", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0097", "term": "Nucleic acid structure analysis" }, { "uri": "http://edamontology.org/topic_0099", "term": "RNA" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "MATLAB", "C++", "C#", "JavaScript", "PHP", "Bash", "Python", "Java", "SQL" ], "license": "Freeware", "collectionID": [ "Czech Republic", "ELIXIR-CZ" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data", "Tools" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/handrbaal/cppredict/", "type": [ "Repository" ], "note": "Prediction algorithm" }, { "url": "http://rpredictordb.elixir-czech.cz/contact", "type": [ "Mailing list" ], "note": null }, { "url": "http://rpredictordb.elixir-czech.cz/search", "type": [ "Service" ], "note": null }, { "url": "http://rpredictordb.elixir-czech.cz/predict#cppredict2", "type": [ "Service" ], "note": null } ], "download": [ { "url": "https://github.com/handrbaal/cppredict/", "type": "Source code", "note": null, "version": null }, { "url": "http://rpredictordb.elixir-czech.cz/download", "type": "Downloads page", "note": null, "version": null } ], "documentation": [ { "url": "http://rpredictor.ms.mff.cuni.cz/documentation/", "type": [ "General", "Citation instructions", "Release notes", "Quick start guide" ], "note": null }, { "url": "http://rpredictordb.elixir-czech.cz/documentation/terms.html", "type": [ "Code of conduct", "Terms of use" ], "note": null }, { "url": "http://rpredictordb.elixir-czech.cz/documentation/rDoc-User/FAQ.html", "type": [ "FAQ" ], "note": null }, { "url": "http://rpredictordb.elixir-czech.cz/documentation/rDoc-Technical/setup.html", "type": [ "Installation instructions" ], "note": null }, { "url": "http://rpredictordb.elixir-czech.cz/documentation/rDoc-User/index.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/database/baz047", "pmid": "31032840", "pmcid": "PMC6482342", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "RPredictorDB: A predictive database of individual secondary structures of RNAs and their formatted plots", "abstract": "© 2019 The Author(s) 2019. Published by Oxford University Press.Secondary data structure of RNA molecules provides insights into the identity and function of RNAs. With RNAs readily sequenced, the question of their structural characterization is increasingly important. However, RNA structure is difficult to acquire. Its experimental identification is extremely technically demanding, while computational prediction is not accurate enough, especially for large structures of long sequences. We address this difficult situation with rPredictorDB, a predictive database of RNA secondary structures that aims to form a middle ground between experimentally identified structures in PDB and predicted consensus secondary structures in Rfam. The database contains individual secondary structures predicted using a tool for template-based prediction of RNA secondary structure for the homologs of the RNA families with at least one homolog with experimentally solved structure. Experimentally identified structures are used as the structural templates and thus the prediction has higher reliability than de novo predictions in Rfam. The sequences are downloaded from public resources. So far rPredictorDB covers 7365 RNAs with their secondary structures. Plots of the secondary structures use the Traveler package for readable display of RNAs with long sequences and complex structures, such as ribosomal RNAs. The RNAs in the output of rPredictorDB are extensively annotated and can be viewed, browsed, searched and downloaded according to taxonomic, sequence and structure data. Additionally, structure of user-provided sequences can be predicted using the templates stored in rPredictorDB.", "date": "2019-01-01T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Jelinek J." }, { "name": "Hoksza D." }, { "name": "Hajic J." }, { "name": "Pesek J." }, { "name": "Drozen J." }, { "name": "Hladik T." }, { "name": "Klimpera M." }, { "name": "Vohradsky J." }, { "name": "Panek J." } ], "journal": "Database" } }, { "doi": "10.1109/BIBM.2014.6999394", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": "0.1", "note": "Early version of the prediction algorithm", "metadata": { "title": "Template-based prediction of ribosomal RNA secondary structure", "abstract": "© 2014 IEEE.Determining the structure of ribosomal RNAs (rRNAs) is one of the crucial steps in understanding the process of protein synthesis, for which rRNAs are one of the basic components. Nevertheless, due to extreme technical difficulties, spatial (3D) structures have been resolved experimentally for only 14 organisms. Also, computational prediction of 3D rRNA structure is almost impossible, and prediction of secondary structure (the list of base pairs in the folded RNA), an important intermediate step between sequence and 3D structure that is used broadly in modeling of RNA structures, is in the case of rRNAs hindered by both extreme sequence length and high structure complexity. Here we present a proof-of-concept for an rRNA secondary structure prediction method that utilizes known structures as structural templates. Our template-based prediction algorithm determines those regions of the sequence for which structure is being predicted that are conserved well enough so that their secondary structure can be copied over from the template. The structure of the remaining, unconserved regions is predicted using a thermodynamic folding model. Applying a baseline implementation of our algorithm to the E. coli 16S rRNA, we have achieved state-of-the-art recall and precision using the structure of T. thermophilus 16S rRNA as a template.", "date": "2014-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Panek J." }, { "name": "Hajic J." }, { "name": "Hoksza D." } ], "journal": "Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014" } }, { "doi": "10.3389/fgene.2017.00147", "pmid": "29067038", "pmcid": "PMC5641303", "type": [ "Method" ], "version": "1.0", "note": "Final version of the prediction algorithm", "metadata": { "title": "An algorithm for template-based prediction of secondary structures of individual RNA sequences", "abstract": "© 2017 Pánek, Modrák and Schwarz.While understanding the structure of RNA molecules is vital for deciphering their functions, determining RNA structures experimentally is exceptionally hard. At the same time, extant approaches to computational RNA structure prediction have limited applicability and reliability. In this paper we provide a method to solve a simpler yet still biologically relevant problem: prediction of secondary RNA structure using structure of different molecules as a template. Our method identifies conserved and unconserved subsequences within an RNA molecule. For conserved subsequences, the template structure is directly transferred into the generated structure and combined with de-novo predicted structure for the unconserved subsequences with low evolutionary conservation. The method also determines, when the generated structure is unreliable. The method is validated using experimentally identified structures. The accuracy of the method exceeds that of classical prediction algorithms and constrained prediction methods. This is demonstrated by comparison using large number of heterogeneous RNAs. The presented method is fast and robust, and useful for various applications requiring knowledge of secondary structures of individual RNA sequences.", "date": "2017-10-10T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Panek J." }, { "name": "Modrak M." }, { "name": "Schwarz M." } ], "journal": "Frontiers in Genetics" } }, { "doi": "10.1186/s12859-017-1885-4", "pmid": "29141608", "pmcid": "PMC5688744", "type": [ "Method" ], "version": null, "note": "Visualisation tool", "metadata": { "title": "TRAVeLer: A tool for template-based RNA secondary structure visualization", "abstract": "© 2017 The Author(s).Background: Visualization of RNA secondary structures is a complex task, and, especially in the case of large RNA structures where the expected layout is largely habitual, the existing visualization tools often fail to produce suitable visualizations. This led us to the idea to use existing layouts as templates for the visualization of new RNAs similarly to how templates are used in homology-based structure prediction. Results: This article introduces Traveler, a software tool enabling visualization of a target RNA secondary structure using an existing layout of a sufficiently similar RNA structure as a template. Traveler is based on an algorithm which converts the target and template structures into corresponding tree representations and utilizes tree edit distance coupled with layout modification operations to transform the template layout into the target one. Traveler thus accepts a pair of secondary structures and a template layout and outputs a layout for the target structure. Conclusions: Traveler is a command-line open source tool able to quickly generate layouts for even the largest RNA structures in the presence of a sufficiently similar layout. It is available at http://github.com/davidhoksza/traveler.", "date": "2017-11-15T00:00:00Z", "citationCount": 10, "authors": [ { "name": "Elias R." }, { "name": "Hoksza D." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-CZ", "email": null, "url": "https://www.elixir-czech.cz/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "David Hoksza", "email": "david.hoksza@gmail.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Josef Pánek", "email": "panek@biomed.cas.cz", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer" ], "note": null } ], "owner": "ELIXIR-CZ", "additionDate": "2015-12-02T14:55:21Z", "lastUpdate": "2021-05-15T10:41:27Z", "editPermission": { "type": "group", "authors": [ "jelinek" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "OntoBrowser", "description": "The tool was developed to manage ontologies (and controlled terminologies e.g. CDISC SEND). The primary goal of the tool is to provide an online collaborative solution for expert curators to map code list terms (sourced from multiple systems/databases) to preferred ontology terms. Other key features include visualisation of ontologies in hierarchical/graph format, advanced search capabilities, peer review/approval workflow and web service access to data.", "homepage": "https://github.com/Novartis/ontobrowser", "biotoolsID": "ontobrowser", "biotoolsCURIE": "biotools:ontobrowser", "version": [ "1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_3559", "term": "Ontology visualisation" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_2429", "term": "Mapping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_2549", "term": "OBO" } ] }, { "data": { "uri": "http://edamontology.org/data_0966", "term": "Ontology term" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2254", "term": "OBO file format name" }, "format": [ { "uri": "http://edamontology.org/format_3262", "term": "OWL/XML" }, { "uri": "http://edamontology.org/format_3255", "term": "Turtle" }, { "uri": "http://edamontology.org/format_3253", "term": "Manchester OWL Syntax" }, { "uri": "http://edamontology.org/format_3261", "term": "RDF/XML" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] } ], "note": "Web based collaborative ontology curation\nInteractive hierarchical/graph visualisation\nCross ontology searching\nSynonym mapping\nAutomated mapping of similar matching synonyms\nCentral database for all ontologies\nVersion tracking\nReview/Approve workflow\nEmail notification\nFull curator audit trail/history Ontologies can be loaded into OntoBrowser using the /ontobrowser/ontologies RESTful web service. The web service only supports the PUT method for loading ontologies and only accepts OBO formatted data.\nhttps://github.com/Novartis/ontobrowser/blob/master/doc/INSTALL.md Verbatim terms (to be reconcilated) are loaded from remote source database.\nControlled vocabularies are loaded via SQL. The following Internet Media Types are supported by the web service for GET requests:\napplication/rdf+xml\napplication/owl+xml\ntext/owl-manchester\ntext/turtle\ntext/obo\napplication/obo\napplication/json\nhttps://github.com/Novartis/ontobrowser/blob/master/doc/web_services.md", "cmd": null } ], "toolType": [ "Web API", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" }, { "uri": "http://edamontology.org/topic_3345", "term": "Data identity and mapping" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "SQL" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Novartis/ontobrowser", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/Novartis/ontobrowser/blob/master/LICENSE.txt", "type": [ "Terms of use" ], "note": null }, { "url": "https://github.com/Novartis/ontobrowser/tree/master/doc", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btw579", "pmid": "27605099", "pmcid": "PMC5408772", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "OntoBrowser: A collaborative tool for curation of ontologies by subject matter experts", "abstract": "© The Author 2016. Published by Oxford University Press.The lack of controlled terminology and ontology usage leads to incomplete search results and poor interoperability between databases. One of the major underlying challenges of data integration is curating data to adhere to controlled terminologies and/or ontologies. Finding subject matter experts with the time and skills required to perform data curation is often problematic. In addition, existing tools are not designed for continuous data integration and collaborative curation. This results in time-consuming curation workflows that often become unsustainable. The primary objective of OntoBrowser is to provide an easy-to-use online collaborative solution for subject matter experts to map reported terms to preferred ontology (or code list) terms and facilitate ontology evolution. Additional features include web service access to data, visualization of ontologies in hierarchical/graph format and a peer review/approval workflow with alerting.", "date": "2017-01-01T00:00:00Z", "citationCount": 13, "authors": [ { "name": "Ravagli C." }, { "name": "Pognan F." }, { "name": "Marc P." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Carlo Ravagli", "email": null, "url": "http://opensource.nibr.com", "orcidid": null, "gridid": "grid.419481.1", "rorid": "02f9zrr09", "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Francois Pognan", "email": null, "url": "http://opensource.nibr.com", "orcidid": "https://orcid.org/0000-0001-7033-2033", "gridid": "grid.419481.1", "rorid": "02f9zrr09", "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Philippe Marc", "email": "philippe.marc@novartis.com", "url": "http://opensource.nibr.com", "orcidid": "https://orcid.org/0000-0002-0064-0572", "gridid": "grid.419481.1", "rorid": "02f9zrr09", "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Primary contact" ], "note": null }, { "name": "Innovative Medicines Initiative (IMI)", "email": null, "url": "https://www.imi.europa.eu", "orcidid": null, "gridid": "grid.454814.8", "rorid": "019af4n30", "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": "Innovative Medicines Initiative Joint Undertaking under grant agreement n° 115002. Part of the eTOX project (http://www.etoxproject.eu)" } ], "owner": "pmarcpub@free.fr", "additionDate": "2016-07-08T14:20:47Z", "lastUpdate": "2021-01-11T08:26:53Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "StPeter", "description": "A tool for analyzing proteomics data acquired by mass spectrometry. Quantifies proteins from shotgun MS/MS data using normalized spectral count or normalized spectral index techniques. Incorporates distributed techniques to account for peptide sequence degeneracy.", "homepage": "http://tppms.org", "biotoolsID": "stpeter", "biotoolsCURIE": "biotools:stpeter", "version": [ "1.4.0" ], "otherID": [], "relation": [ { "biotoolsID": "tpp_spc", "type": "includedIn" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3637", "term": "Spectral counting" }, { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" }, { "uri": "http://edamontology.org/operation_3630", "term": "Protein quantification" }, { "uri": "http://edamontology.org/operation_3634", "term": "Label-free quantification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [ { "uri": "http://edamontology.org/format_3747", "term": "protXML" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [ { "uri": "http://edamontology.org/format_3747", "term": "protXML" } ] } ], "note": "Output file is the same protXML input file, but with protein quantification results appended to each protein group.", "cmd": "StPeter myProteins.prot.xml" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1021/acs.jproteome.7b00786", "pmid": "29400476", "pmcid": "PMC5891225", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "StPeter: Seamless Label-Free Quantification with the Trans-Proteomic Pipeline", "abstract": "© 2018 American Chemical Society.Label-free quantification has grown in popularity as a means of obtaining relative abundance measures for proteomics experiments. However, easily accessible and integrated tools to perform label-free quantification have been lacking. We describe StPeter, an implementation of Normalized Spectral Index quantification for wide availability through integration into the widely used Trans-Proteomic Pipeline. This implementation has been specifically designed for reproducibility and ease of use. We demonstrate that StPeter outperforms other state-of-the art packages using a recently reported benchmark data set over the range of false discovery rates relevant to shotgun proteomics results. We also demonstrate that the software is computationally efficient and supports data from a variety of instrument platforms and experimental designs. Results can be viewed within the Trans-Proteomic Pipeline graphical user interfaces and exported in standard formats for downstream statistical analysis. By integrating StPeter into the freely available Trans-Proteomic Pipeline, users can now obtain high-quality label-free quantification of any data set in seconds by adding a single command to the workflow.", "date": "2018-03-02T00:00:00Z", "citationCount": 11, "authors": [ { "name": "Hoopmann M.R." }, { "name": "Winget J.M." }, { "name": "Mendoza L." }, { "name": "Moritz R.L." } ], "journal": "Journal of Proteome Research" } } ], "credit": [], "owner": "mhoopmann", "additionDate": "2020-12-20T16:40:10Z", "lastUpdate": "2020-12-21T16:38:53Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "pbg-ld", "description": "Linked Data platform for Plant Breeding & Genomics", "homepage": "https://www.research-software.nl/software/pbg-ld", "biotoolsID": "pbg-ld", "biotoolsCURIE": "biotools:pbg-ld", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_0361", "term": "Sequence annotation" }, { "uri": "http://edamontology.org/operation_3282", "term": "ID mapping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2376", "term": "RDF format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "SPARQL endpoint", "Web API" ], "topic": [ { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_0797", "term": "Comparative genomics" }, { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Other" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Emerging", "cost": null, "accessibility": "Open access", "elixirPlatform": [ "Data" ], "elixirNode": [ "Netherlands" ], "elixirCommunity": [], "link": [ { "url": "https://www.research-software.nl/software/pbg-ld", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/candYgene/pbg-ld", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/candYgene/pbg-ld/blob/master/README.md", "type": [ "Installation instructions" ], "note": null } ], "publication": [ { "doi": "10.18174/FAIRdata2018.16287", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": null }, { "doi": "10.3390/app10196813", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Linked data platform for solanaceae species", "abstract": "© 2020 by the authors.Genetics research is increasingly focusing on mining fully sequenced genomes and their annotations to identify the causal genes associated with traits (phenotypes) of interest. However, a complex trait is typically associated with multiple quantitative trait loci (QTLs), each comprising many genes, that can positively or negatively affect the trait of interest. To help breeders in ranking candidate genes, we developed an analytical platform called pbg-ld that provides semantically integrated geno- and phenotypic data on Solanaceae species. This platform combines both unstructured data from scientific literature and structured data from publicly available biological databases using the Linked Data approach. In particular, QTLs were extracted from tables of full-text articles from the Europe PubMed Central (PMC) repository using QTLTableMiner++ (QTM), while the genomic annotations were obtained from the Sol Genomics Network (SGN), UniProt and Ensembl Plants databases. These datasets were transformed into Linked Data graphs, which include cross-references to many other relevant databases such as Gramene, Plant Reactome, InterPro and KEGG Orthology (KO). Users can query and analyze the integrated data through a web interface or programmatically via the SPARQL and RESTful services (APIs). We illustrate the usability of pbg-ld by querying genome annotations, by comparing genome graphs, and by two biological use cases in Jupyter Notebooks. In the first use case, we performed a comparative genomics study using pbg-ld to compare the difference in the genetic mechanism underlying tomato fruit shape and potato tuber shape. In the second use case, we developed a seamlessly integrated workflow that uses genomic data from pbg-ld knowledge graphs and prioritization pipelines to predict candidate genes within QTL regions for metabolic traits of tomato.", "date": "2020-10-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Singh G." }, { "name": "Kuzniar A." }, { "name": "Brouwer M." }, { "name": "Martinez-Ortiz C." }, { "name": "Bachem C.W.B." }, { "name": "Tikunov Y.M." }, { "name": "Bovy A.G." }, { "name": "Visser R.G.F." }, { "name": "Finkers R." } ], "journal": "Applied Sciences (Switzerland)" } }, { "doi": "10.5281/zenodo.1458168", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Arnold Kuzniar", "email": "a.kuzniar@esciencecenter.nl", "url": null, "orcidid": "https://orcid.org/0000-0003-1711-7961", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer", "Primary contact" ], "note": null }, { "name": "Carlos Martinez-Ortiz", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-5565-7577", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Gurnoor Singh", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-1615-4197", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Richard VIsser", "email": "richard.visser@wur.nl", "url": null, "orcidid": "https://orcid.org/0000-0002-0213-4016", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Richard Finkers", "email": "richard.finkers@wur.nl", "url": null, "orcidid": "https://orcid.org/0000-0002-4368-8058", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "arnikz", "additionDate": "2020-04-26T10:21:33Z", "lastUpdate": "2020-10-16T21:41:22Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BLAST DataBase Manager", "description": "Graphical user interface that allows you to create high quality sequence datasets using the tools included. Using these tools you can perform several common tasks such as doing BLAST alignments, getting the open reading frames of the sequences in a Fasta file or changing the format of a Fasta file. All these task make use of several known tools such as EMBOSS, bedtools, and NCBI's BLAST, Splign and Compart.", "homepage": "http://www.sing-group.org/BDBM", "biotoolsID": "bdbm", "biotoolsCURIE": "biotools:bdbm", "version": [ "1.0.2" ], "otherID": [], "relation": [ { "biotoolsID": "blast", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_3071", "term": "Data management" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": "GPL-3.0", "collectionID": [ "BLAST utility" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/sing-group/BDBM/", "type": "Source code", "note": null, "version": null }, { "url": "http://www.sing-group.org/BDBM/download.html", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "http://www.sing-group.org/BDBM/manual.html", "type": [ "User manual" ], "note": null }, { "url": "http://www.sing-group.org/BDBM/usecases.html", "type": [ "Training material" ], "note": null } ], "publication": [ { "doi": "10.1007/s12539-019-00320-3", "pmid": "30712176", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "BDBM 1.0: A Desktop Application for Efficient Retrieval and Processing of High-Quality Sequence Data and Application to the Identification of the Putative Coffea S-Locus", "abstract": "© 2019, International Association of Scientists in the Interdisciplinary Areas.Nowadays, bioinformatics is one of the most important areas in modern biology and the creation of high-quality scientific software supporting this recent research area is one of the core activities of many researchers. In this context, high-quality sequence datasets are needed to perform inferences on the evolution of species, genes, and gene families, or to get evidence for adaptive amino acid evolution, among others. Nevertheless, sequence data are very often spread over several databases, many useful genomes and transcriptomes are non-annotated, the available annotation is not for the desired coding sequence isoform, and/or is unlikely to be accurate. Moreover, although the FASTA text-based format is quite simple and usable by most software applications, there are a number of issues that may be critical depending on the software used to analyse such files. Therefore, researchers without training in informatics often use a fraction of all available data. The above issues can be addressed using already available software applications, but there is no easy-to-use single piece of software that allows performing all these tasks within the same graphical interface, such as the one here presented, named BDBM (Blast DataBase Manager). BDBM can be used to efficiently get gene sequences from annotated and non-annotated genomes and transcriptomes. Moreover, it can be used to look for alternatives to existing annotations and to easily create reliable custom databases. Such databases are essential to prepare high-quality datasets. The analyses that we have performed on the Coffea canephora genome using BDBM aimed at the identification of the S-locus region (that harbours the genes involved in gametophytic self-incompatibility) led to the conclusion that there are two likely regions, one on chromosome 2 (around region 6600000–6650000), and another on chromosome 5 (around 15830000–15930000). Such findings are discussed in the context of the Rubiaceae gametophytic self-incompatibility evolution.", "date": "2019-03-01T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Vazquez N." }, { "name": "Lopez-Fernandez H." }, { "name": "Vieira C.P." }, { "name": "Fdez-Riverola F." }, { "name": "Vieira J." }, { "name": "Reboiro-Jato M." } ], "journal": "Interdisciplinary Sciences: Computational Life Sciences" } } ], "credit": [ { "name": "Molecular Evolution Group (IBMC)", "email": null, "url": "http://evolution.ibmc.up.pt/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "SING Research Group", "email": null, "url": "http://www.sing-group.org", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null }, { "name": null, "email": null, "url": "http://www.sing-group.org/BDBM/about.html", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "hlfernandez@uvigo.es", "additionDate": "2017-01-11T12:47:54Z", "lastUpdate": "2020-06-16T10:55:24Z", "editPermission": { "type": "group", "authors": [ "jbvieira" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DeltaMass", "description": "Automated detection and visualization of mass shifts in proteomic open search results.", "homepage": "https://github.com/chhh/deltamass", "biotoolsID": "deltamass", "biotoolsCURIE": "biotools:deltamass", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3215", "term": "Peak detection" }, { "uri": "http://edamontology.org/operation_3627", "term": "Mass spectra calibration" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrometry spectra" }, "format": [ { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" } ] }, { "data": { "uri": "http://edamontology.org/data_0945", "term": "Peptide identification" }, "format": [ { "uri": "http://edamontology.org/format_3655", "term": "pepXML" }, { "uri": "http://edamontology.org/format_3247", "term": "mzIdentML" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0844", "term": "Molecular mass" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": "GPL-3.0", "collectionID": [ "Proteomics" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/chhh/deltamass/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/chhh/deltamass/releases", "type": "Software package", "note": "Windows binaries also available", "version": null } ], "documentation": [ { "url": "https://github.com/chhh/deltamass/blob/master/README.md", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jproteome.8b00728.", "pmid": "30523686", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "DeltaMass: Automated Detection and Visualization of Mass Shifts in Proteomic Open-Search Results", "abstract": "Copyright © 2018 American Chemical Society.Routine identification of thousands of proteins in a single LC-MS experiment has long become the norm. With these vast amounts of data, more rigorous treatment of modified forms of peptides becomes possible. \"Open search\", a protein database search with a large precursor ion mass tolerance window, is becoming a popular method to evaluate possible sets of post-translational and chemical modifications in samples. The extraction of statistical information about the modification from peptide search results requires additional effort and data processing, such as recalibration of masses and accurate detection of precursors in MS1 signals. Here we present a software tool, DeltaMass, which performs kernel-density-based estimation of observed mass shifts and allows for the detection of poorly resolved mass deltas. The software also maps observed mass shifts to known modifications from public databases such as UniMod and augments them with additionally generated possible chemical changes to the molecule. Its interactive graphical interface provides an effective option for the visual interrogation of the data and the identification of potentially interesting mass shifts or unusual artifacts for subsequent analysis. However, the program can also be used in fully automated command-line mode to generate mass-shift peak lists as well.", "date": "2019-02-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Avtonomov D.M." }, { "name": "Kong A." }, { "name": "Nesvizhskii A.I." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Dmitry Avtonomov", "email": null, "url": "http://dmtavt.com/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2019-01-16T15:57:27Z", "lastUpdate": "2020-06-16T10:55:24Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "GenIO", "description": "Genomic Input Output (GenIO) identifies the most probable variants causing a rare disease, using the genomic and clinical information provided by a medical practitioner.", "homepage": "https://bioinformatics.ibioba-mpsp-conicet.gov.ar/GenIO/index.php", "biotoolsID": "GenIO", "biotoolsCURIE": "biotools:GenIO", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3229", "term": "Exome assembly" }, { "uri": "http://edamontology.org/operation_3196", "term": "Genotyping" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" }, { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_3676", "term": "Exome sequencing" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "PHP", "JavaScript" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Restricted access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://bioinformatics.ibioba-mpsp-conicet.gov.ar/GenIO/help.htm", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1186/s12859-018-2027-3", "pmid": "29374474", "pmcid": "PMC5787240", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "GenIO: A phenotype-genotype analysis web server for clinical genomics of rare diseases", "abstract": "© 2018 The Author(s).Background: GenIO is a novel web-server, designed to assist clinical genomics researchers and medical doctors in the diagnostic process of rare genetic diseases. The tool identifies the most probable variants causing a rare disease, using the genomic and clinical information provided by a medical practitioner. Variants identified in a whole-genome, whole-exome or target sequencing studies are annotated, classified and filtered by clinical significance. Candidate genes associated with the patient's symptoms, suspected disease and complementary findings are identified to obtain a small manageable number of the most probable recessive and dominant candidate gene variants associated with the rare disease case. Additionally, following the American College of Medical Genetics and Genomics and the Association of Molecular Pathology (ACMG-AMP) guidelines and recommendations, all potentially pathogenic variants that might be contributing to disease and secondary findings are identified. Results: A retrospective study was performed on 40 patients with a diagnostic rate of 40%. All the known genes that were previously considered as disease causing were correctly identified in the final inherit model output lists. In previously undiagnosed cases, we had no additional yield. Conclusion: This unique, intuitive and user-friendly tool to assists medical doctors in the clinical genomics diagnostic process is openly available at https://bioinformatics.ibioba-mpsp-conicet.gov.ar/GenIO/.", "date": "2018-01-27T00:00:00Z", "citationCount": 4, "authors": [ { "name": "Koile D." }, { "name": "Cordoba M." }, { "name": "de Sousa Serro M." }, { "name": "Kauffman M.A." }, { "name": "Yankilevich P." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": null, "email": "genio@ibioba-mpsp-conicet.gov.ar", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Project", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Ruta", "additionDate": "2019-05-10T06:47:52Z", "lastUpdate": "2020-06-16T10:55:23Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Phen-Gen", "description": "Combines patients' disease symptoms and sequencing data with prior domain knowledge to identify the causative genes for rare disorders.", "homepage": "http://phen-gen.org/", "biotoolsID": "Phen-Gen", "biotoolsCURIE": "biotools:Phen-Gen", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3501", "term": "Enrichment analysis" }, { "uri": "http://edamontology.org/operation_0487", "term": "Haplotype mapping" }, { "uri": "http://edamontology.org/operation_3196", "term": "Genotyping" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Perl" ], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1038/nmeth.3046", "pmid": "25086502", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Phen-gen: Combining phenotype and genotype to analyze rare disorders", "abstract": "We introduce Phen-Gen, a method that combines patients' disease symptoms and sequencing data with prior domain knowledge to identify the causative genes for rare disorders. Simulations revealed that the causal variant was ranked first in 88% of cases when it was a coding variant-a 52% advantage over a genotype-only approach-and Phen-Gen outperformed other existing prediction methods by 13-58%. If disease etiology was unknown, the causal variant was assigned the top rank in 71% of simulations. Phen-Gen is available at http://phen-gen.org/.", "date": "2014-01-01T00:00:00Z", "citationCount": 83, "authors": [ { "name": "Javed A." }, { "name": "Agrawal S." }, { "name": "Ng P.C." } ], "journal": "Nature Methods" } } ], "credit": [ { "name": null, "email": null, "url": "http://www.phen-gen.com/phengencontactus.php", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Project", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Ruta", "additionDate": "2019-05-11T07:49:33Z", "lastUpdate": "2020-06-16T10:55:21Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null } ] }