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{ "count": 47, "next": null, "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": "openVRE", "description": "The Open Virtual Research Environment is a general purpose analysis platform that can be tailored for domain specific analyses.", "homepage": "https://github.com/inab/openVRE/wiki", "biotoolsID": "openvre", "biotoolsCURIE": "biotools:openvre", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "mugvre", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3760", "term": "Service management" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Bioinformatics portal", "Workbench" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Linux" ], "language": [ "PHP", "Python", "JavaScript" ], "license": "Apache-2.0", "collectionID": [ "EUCAIM" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Spain" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/inab/openVRE", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [ { "url": "http://vre.multiscalegenomics.eu/help/starting.php", "type": [ "Quick start guide" ], "note": "Getting Started Guide" } ], "publication": [], "credit": [ { "name": "Laia Codó", "email": "laia.codo@bsc.es", "url": "https://www.bsc.es/codo-laia", "orcidid": "https://orcid.org/0000-0002-6797-8746", "gridid": "grid.10097.3f", "rorid": "05sd8tv96", "fundrefid": "10.13039/501100006433", "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "Senior Researcher at Barcelona Supercomputing Center. Lead of Trusted Research Environments and Cloud Computing at INB Lab." }, { "name": "Josep Lluís Gelpí", "email": "gelpi@ub.edu", "url": "https://webgrec.ub.edu/webpages/000011/ang/gelpi.ub.edu.html", "orcidid": "http://orcid.org/0000-0002-0566-7723", "gridid": "grid.5841.8", "rorid": "021018s57", "fundrefid": "10.13039/501100005774", "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Professor at University of Barcelona and Team Leader at BSC's INB Laboratory" } ], "owner": "gelpi@ub.edu", "additionDate": "2025-04-16T08:53:57.270825Z", "lastUpdate": "2025-04-16T08:53:57.280528Z", "editPermission": { "type": "group", "authors": [ "gelpi@ub.edu" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PinMol", "description": "Application for designing molecular beacons for live cell imaging of endogenous mRNAs.", "homepage": "https://bratulab.wordpress.com/software/", "biotoolsID": "PinMol", "biotoolsCURIE": "biotools:PinMol", "version": [ "beta 1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0278", "term": "RNA secondary structure prediction" }, { "uri": "http://edamontology.org/operation_0502", "term": "RNA secondary structure alignment" }, { "uri": "http://edamontology.org/operation_0279", "term": "Nucleic acid folding analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" }, { "uri": "http://edamontology.org/topic_0632", "term": "Probes and primers" }, { "uri": "http://edamontology.org/topic_3382", "term": "Imaging" } ], "operatingSystem": [ "Windows", "Mac" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/icatrina/PinMol_Win/releases/tag/v1.0-beta", "type": "Source code", "note": null, "version": "beta 1.0" }, { "url": "https://github.com/icatrina/PinMol_Mac/releases/tag/v1.0-beta", "type": "Source code", "note": null, "version": "beta 1.0" } ], "documentation": [ { "url": "https://bratulab.wordpress.com/tutorial-pinmol-mac/", "type": [ "Training material" ], "note": "Tutorial material" } ], "publication": [ { "doi": "10.1261/rna.069542.118", "pmid": "30573696", "pmcid": "PMC6380279", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Pinmol: Python application for designing molecular beacons for live cell imaging of endogenous mRNAs", "abstract": "Molecular beacons are nucleic acid oligomers labeled with a fluorophore and a quencher that fold in a hairpin-shaped structure, which fluoresce only when bound to their target RNA. They are used for the visualization of endogenous mRNAs in live cells. Here, we report a Python program (PinMol) that designs molecular beacons best suited for live cell imaging by using structural information from secondary structures of the target RNA, predicted via energy minimization approaches. PinMol takes into account the accessibility of the targeted regions, as well as the inter- and intramolecular interactions of each selected probe. To demonstrate its applicability, we synthesized an oskar mRNA-specific molecular beacon (osk1236), which is selected by PinMol to target a more accessible region than a manually designed oskar-specific molecular beacon (osk2216). We previously demonstrated osk2216 to be efficient in detecting oskar mRNA in in vivo experiments. Here, we show that osk1236 outperformed osk2216 in live cell imaging experiments.", "date": "2019-03-01T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Bayer L.V." }, { "name": "Omar O.S." }, { "name": "Bratu D.P." }, { "name": "Catrina I.E." } ], "journal": "RNA" } } ], "credit": [ { "name": "Irina E. Catrina", "email": "iecatrina@gmail.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Ruta", "additionDate": "2019-05-27T16:33:42Z", "lastUpdate": "2024-11-25T13:45:28.770486Z", "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": "iS-CellR", "description": "iS-CellR (Interactive platform for Single-cell RNAseq) is a web-based Shiny application designed to provide a comprehensive analysis of single-cell RNA sequencing data.", "homepage": "https://github.com/immcore/iS-CellR", "biotoolsID": "iS-CellR", "biotoolsCURIE": "biotools:iS-CellR", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3196", "term": "Genotyping" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_0099", "term": "RNA" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/immcore/iS-CellR/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/immcore/iS-CellR/releases/tag/v1.1", "type": "Source code", "note": null, "version": "1.1" }, { "url": "https://github.com/immcore/iS-CellR/releases/tag/v1.0", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://github.com/immcore/iS-CellR/blob/master/README.md", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/bty517", "pmid": "29982379", "pmcid": "PMC6289135", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "iS-CellR: A user-friendly tool for analyzing and visualizing single-cell RNA sequencing data", "abstract": "Interactive platform for single-cell RNA-sequencing (iS-CellR) is a web-based Shiny application that is designed to provide user-friendly, comprehensive analysis of single-cell RNA sequencing data. iS-CellR has the capability to run on any modern web browser and provides an accessible graphical user interface that enables the user to perform complex single-cell RNA-sequencing analysis without requiring programming skills.", "date": "2018-12-15T00:00:00Z", "citationCount": 15, "authors": [ { "name": "Patel M.V." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Mitulkumar V. Patel", "email": "mitul.patel@immunocore.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Ruta", "additionDate": "2019-07-06T07:28:17Z", "lastUpdate": "2024-11-24T21:07:42.254501Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Adjutant", "description": "R-based tool to support topic discovery for systematic and literature reviews.", "homepage": "https://github.com/amcrisan/Adjutant", "biotoolsID": "Adjutant", "biotoolsCURIE": "biotools:Adjutant", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0306", "term": "Text mining" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3068", "term": "Literature and language" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "R" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/amcrisan/Adjutant/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/amcrisan/Adjutant/releases", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://github.com/amcrisan/Adjutant/blob/master/README.md", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/bty722", "pmid": "30875428", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Adjutant: An R-based tool to support topic discovery for systematic and literature reviews", "abstract": "Adjutant is an open-source, interactive and R-based application to support mining PubMed for literature reviews. Given a PubMed-compatible search query, Adjutant downloads the relevant articles and allows the user to perform an unsupervised clustering analysis to identify data-driven topic clusters. Following clustering, users can also sample documents using different strategies to obtain a more manageable dataset for further analysis. Adjutant makes explicit trade-offs between speed and accuracy, which are modifiable by the user, such that a complete analysis of several thousand documents can take a few minutes. All analytic datasets generated by Adjutant are saved, allowing users to easily conduct other downstream analyses that Adjutant does not explicitly support.", "date": "2019-03-15T00:00:00Z", "citationCount": 13, "authors": [ { "name": "Crisan A." }, { "name": "Munzner T." }, { "name": "Gardy J.L." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Anamaria Crisan", "email": "acrisan@cs.ubc.ca", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Ruta", "additionDate": "2019-07-06T06:25:02Z", "lastUpdate": "2024-11-24T21:07:34.125543Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DNAtools", "description": "Includes predicting DNA curvature; plotting physicochemical, statistical, or locally computed paramaters along DNA sequences; producing a 3-D model of a DNA sequence; searching an intron database.", "homepage": "http://pongor.itk.ppke.hu/?q=bioinfoservices", "biotoolsID": "dnatools", "biotoolsCURIE": "biotools:dnatools", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0550", "term": "DNA substitution modelling" }, { "uri": "http://edamontology.org/operation_0433", "term": "Splice site prediction" }, { "uri": "http://edamontology.org/operation_2499", "term": "Splicing model analysis" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" }, { "uri": "http://edamontology.org/topic_0654", "term": "DNA" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_0082", "term": "Structure prediction" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "Unlicense", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://pongor.itk.ppke.hu/dna/plot_it.html#/plotit_form", "type": [ "Service" ], "note": "plot.it® Server: The Form" }, { "url": "http://pongor.itk.ppke.hu/dna/bend_it.html#/bendit_form", "type": [ "Service" ], "note": "bend.it® Server" }, { "url": "http://pongor.itk.ppke.hu/dna/model_it.html#/modelit_form", "type": [ "Service" ], "note": "model.it® Server" } ], "download": [ { "url": "https://github.com/r78v10a07/bendit/archive/1.0.tar.gz", "type": "Software package", "note": "Bend.it® Standalone version", "version": "1.0" } ], "documentation": [ { "url": "http://pongor.itk.ppke.hu/dna/bend_it.html#/bendit_intro", "type": [ "General" ], "note": "bend.it® Server" }, { "url": "http://pongor.itk.ppke.hu/dna/plot_it.html#/plotit_intro", "type": [ "General" ], "note": "plot.it® Server" }, { "url": "http://pongor.itk.ppke.hu/dna/model_it.html#/modelit_intro", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkg559", "pmid": "12824394", "pmcid": "PMC168966", "type": [], "version": null, "note": null, "metadata": { "title": "DNA analysis servers: Plot.it, bend.it, model.it and IS", "abstract": "The WWW servers at http://www.icgeb.trieste.it/dna/ are dedicated to the analysis of user-submitted DNA sequences; plot.it creates parametric plots of 45 physicochemical, as well as statistical, parameters; bend.it calculates DNA curvature according to various methods. Both programs provide 1D as well as 2D plots that allow localisation of peculiar segments within the query. The server model.it creates 3D models of canonical or bent DNA starting from sequence data and presents the results in the form of a standard PDB file, directly viewable on the user's PC using any molecule manipulation program. The recently established introns server allows statistical evaluation of introns in various taxonomic groups and the comparison of taxonomic groups in terms of length, base composition, intron type etc. The options include the analysis of splice sites and a probability test for exon-shuffling.", "date": "2003-07-01T00:00:00Z", "citationCount": 116, "authors": [ { "name": "Vlahovicek K." }, { "name": "Kajan L." }, { "name": "Pongor S." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Sándor Pongor", "email": "pongor.sandor@itk.ppke.hu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-EE", "additionDate": "2017-03-24T09:34:10Z", "lastUpdate": "2024-11-24T21:03:59.382352Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Isodyn", "description": "“C++”-program simulating the dynamics of metabolites and their isotopic isomers in the central metabolic network using a corresponding kinetic model. Supports the final step of 13C assisted the fluxomic analysis: evaluation of metabolic fluxes consistent with a given mass isotopomer distribution. The previous steps are supported by Ramid, Midcor, Isoform.", "homepage": "https://github.com/seliv55/isodyn", "biotoolsID": "Isodyn", "biotoolsCURIE": "biotools:Isodyn", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_3835", "term": "TIDE TXT" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3835", "term": "TIDE TXT" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_3835", "term": "TIDE TXT" } ] } ], "note": "fiso=\"SW620-Glucose\" # input data: file indicating 13C labeling of metabolites\nfcon=xglc # input data: file with measured concentrations\ninpar=\"glc/1\" # input data: initial set of parameters to start\noudir=\"glc/\" # output directory\nfstat=\"glc/statfl\" # path to write the results of fitting: mean and confidence intervals\nfcmpr=\"glc/statfl\" # results of fitting for the conditions used for comparison.\nmanfi=77 # number of files to be saved during fitting\nFNCKAS # various options for the fitting", "cmd": "./isodyn.out $fiso $fcon $inpar $oudir $fstat $fcmpr $manfi $FNCKAS" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3955", "term": "Fluxomics" } ], "operatingSystem": [ "Linux" ], "language": [ "R" ], "license": "Freeware", "collectionID": [], "maturity": null, "cost": null, "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Spain" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/seliv55/isodyn", "type": [ "Repository" ], "note": "Code and example" } ], "download": [ { "url": "https://github.com/seliv55/isodyn", "type": "Downloads page", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://github.com/seliv55/isodyn", "type": [ "General" ], "note": "Usage instruction and example" } ], "publication": [ { "doi": "10.1007/978-1-0716-0159-4_12", "pmid": "31893378", "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "Software supporting a workflow of quantitative dynamic flux maps estimation in central metabolism from SIRM experimental data", "abstract": "Stable isotope-resolved metabolomics (SIRM), based on the analysis of biological samples from living cells incubated with artificial isotope enriched substrates, enables mapping the rates of biochemical reactions (metabolic fluxes). We developed software supporting a workflow of analysis of SIRM data obtained with mass spectrometry (MS). The evaluation of fluxes starting from raw MS recordings requires at least three steps of computer support: first, extraction of mass spectra of metabolites of interest, then correction of the spectra for natural isotope abundance, and finally, evaluation of fluxes by simulation of the corrected spectra using a corresponding mathematical model. A kinetic model based on ordinary differential equations (ODEs) for isotopomers of metabolites of the corresponding biochemical network supports the final part of the analysis, which provides a dynamic flux map.", "date": "2020-01-01T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Selivanov V.A." }, { "name": "Marin S." }, { "name": "Tarrago-Celada J." }, { "name": "Lane A.N." }, { "name": "Higashi R.M." }, { "name": "Fan T.W.-M." }, { "name": "de Atauri P." }, { "name": "Cascante M." } ], "journal": "Methods in Molecular Biology" } }, { "doi": "10.1093/bioinformatics/bth412", "pmid": "15256408", "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "An optimized algorithm for flux estimation from isotopomer distribution in glucose metabolites", "abstract": "Motivation: Analysis of the conversion of 13C glucose within the metabolic network allows the evaluation of the biochemical fluxes in interconnecting metabolic pathways. Such analyses require solving hundreds of equations with respect to individual isotopomer concentrations, and this assumes applying special software even for constructing the equations. The algorithm, proposed by others could be improved. Method: A C-code linked to the program written in Mathematica (Wolfram Research Inc.), constructs and solves differential equations for all isotopomer concentrations, using the general enzyme characteristics (Km, equilibrium constant, etc.). This code uses innovative algorithm of determination for the isotopomers-products, thus essentially decreasing the computation time. Feasible metabolic fluxes are provided by the parameters of enzyme kinetics found from the data fitting. Results: The software effectively evaluates metabolic fluxes based on the measured isotopomer distribution, as was illustrated by the analysis of glycolysis and pentose phosphate cycle. The mechanism of transketolase and transaldolase catalysis was shown to induce a specific kind of isotopomer re-distribution, which, despite the significance of its effect, usually is not taken into account. © Oxford University Press 2004; all rights reserved.", "date": "2004-12-12T00:00:00Z", "citationCount": 35, "authors": [ { "name": "Selivanov V.A." }, { "name": "Puigjaner J." }, { "name": "Sillero A." }, { "name": "Centelles J.J." }, { "name": "Ramos-Montoya A." }, { "name": "Lee P.W.-N." }, { "name": "Cascante M." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bioinformatics/bti573", "pmid": "16002431", "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "Rapid simulation and analysis of isotopomer distributions using constraints based on enzyme mechanisms: An example from HT29 cancer cells", "abstract": "Motivation: Addition of labeled substrates and the measurement of the subsequent distribution of the labels in isotopomers in reaction networks provide a unique method for assessing metabolic fluxes in whole cells. However, owing to insufficiency of information, attempts to quantify the fluxes often yield multiple possible sets of solutions that are consistent with a given experimental pattern of isotopomers. In the study of the pentose phosphate pathways, the need to consider isotope exchange reactions of transketolase (TK) and transaldolase (TA) (which in past analyses have often been ignored) magnifies this problem; but accounting for the interrelation between the fluxes known from biochemical studies and kinetic modeling solves it. The mathematical relationships between kinetic and equilibrium constants restrict the domain of estimated fluxes to the ones compatible not only with a given set of experimental data, but also with other biochemical information. Method: We present software that integrates kinetic modeling with isotopomer distribution analysis. It solves the ordinary differential equations for total concentrations (accounting for the kinetic mechanisms) as well as for all isotopomers in glycolysis and the pentose phosphate pathway (PPP). In the PPP the fluxes created in the TK and TA reactions are expressed through unitary rate constants. The algorithms that account for all the kinetic and equilbrium constant constraints are integrated with the previously developed algorithms, which have been further optimized. The most time-consuming calculations were programmed directly in assembly language; this gave an order of magnitude decrease in the computation time, thus allowing analysis of more complex systems. The software was developed as C-code linked to a program written in Mathematica (Wolfram Research, Champaign, IL), and also as a C++ program independent from Mathematica. Results: Implementing constraints imposed by kinetic and equilibrium constants in the isotopomer distribution analysis in the data from the cancer cells eliminated estimates of fluxes that were inconsistent with the kinetic mechanisms of TK and TA. Fluxes measured experimentally in cells can be used to estimate better the kinetics of TK and TA as they operate in situ. Thus, our approach of integrating various methods for in situ flux analysis opens up the possibility of designing new types of experiments to probe metabolic interrelationships, including the incorporation of additional biochemical information. © The Author 2005. Published by Oxford University Press. All rights reserved.", "date": "2005-09-01T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Selivanov V.A." }, { "name": "Meshalkina L.E." }, { "name": "Solovjeva O.N." }, { "name": "Kuchel P.W." }, { "name": "Ramos-Montoya A." }, { "name": "Kochetov G.A." }, { "name": "Lee P.W.N." }, { "name": "Cascante M." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bioinformatics/btl484", "pmid": "17000750", "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "Software for dynamic analysis of tracer-based metabolomic data: Estimation of metabolic fluxes and their statistical analysis", "abstract": "Motivation: Metabolic flux analysis of biochemical reaction networks using isotope tracers requires software tools that can analyze the dynamics of isotopic isomer (isotopomer) accumulation in metabolites and reveal the underlying kinetic mechanisms of metabolism regulation. Since existing tools are restricted by the isotopic steady state and remain disconnected from the underlying kinetic mechanisms, we have recently developed a novel approach for the analysis of tracer-based metabolomic data that meets these requirements. The present contribution describes the last step of this development: implementation of (i) the algorithms for the determination of the kinetic parameters and respective metabolic fluxes consistent with the experimental data and (ii) statistical analysis of both fluxes and parameters, thereby lending it a practical application. Results: The C++ applications package for dynamic isotopomer distribution data analysis was supplemented by (i) five distinct methods for resolving a large system of differential equations; (ii) the 'simulated annealing' algorithm adopted to estimate the set of parameters and metabolic fluxes, which corresponds to the global minimum of the difference between the computed and measured isotopomer distributions; and (iii) the algorithms for statistical analysis of the estimated parameters and fluxes, which use the covariance matrix evaluation, as well as Monte Carlo simulations. An example of using this tool for the analysis of 13C distribution in the metabolites of glucose degradation pathways has demonstrated the evaluation of optimal set of parameters and fluxes consistent with the experimental pattern, their range and statistical significance, and also the advantages of using dynamic rather than the usual steady-state method of analysis. © 2006 Oxford University Press.", "date": "2006-11-15T00:00:00Z", "citationCount": 31, "authors": [ { "name": "Selivanov V.A." }, { "name": "Marin S." }, { "name": "Lee P.W.N." }, { "name": "Cascante M." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "vitaly", "additionDate": "2020-01-24T12:37:12Z", "lastUpdate": "2024-11-24T21:00:18.465360Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "RAISS", "description": "software package enabling the imputation of SNP summary statistics from the neighboring SNPs by taking advantage of the Linkage desiquilibrium.", "homepage": "http://statistical-genetics.pages.pasteur.fr/raiss/", "biotoolsID": "raiss", "biotoolsCURIE": "biotools:raiss", "version": [ "1.0, 2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3517", "term": "GWAS study" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" }, { "uri": "http://edamontology.org/topic_3053", "term": "Genetics" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "MIT", "collectionID": [ "Institut Pasteur" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [ { "url": "https://gitlab.pasteur.fr/statistical-genetics/raiss", "type": [ "Repository" ], "note": null }, { "url": "https://gitlab.pasteur.fr/statistical-genetics/raiss/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://biocontainers.pro/#/tools/raiss", "type": "Container file", "note": null, "version": "1.0, 2.0" } ], "documentation": [ { "url": "http://statistical-genetics.pages.pasteur.fr/raiss/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btz466", "pmid": "31173064", "pmcid": "PMC6853677", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "RAISS: Robust and accurate imputation from summary statistics", "abstract": "Multi-trait analyses using public summary statistics from genome-wide association studies (GWASs) are becoming increasingly popular. A constraint of multi-trait methods is that they require complete summary data for all traits. Although methods for the imputation of summary statistics exist, they lack precision for genetic variants with small effect size. This is benign for univariate analyses where only variants with large effect size are selected a posteriori. However, it can lead to strong p-value inflation in multi-trait testing. Here we present a new approach that improve the existing imputation methods and reach a precision suitable for multi-trait analyses. Results: We fine-tuned parameters to obtain a very high accuracy imputation from summary statistics. We demonstrate this accuracy for variants of all effect sizes on real data of 28 GWAS. We implemented the resulting methodology in a python package specially designed to efficiently impute multiple GWAS in parallel.", "date": "2019-11-01T00:00:00Z", "citationCount": 14, "authors": [ { "name": "Julienne H." }, { "name": "Shi H." }, { "name": "Pasaniuc B." }, { "name": "Aschard H." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Hugues Aschard", "email": "hugues.aschard@pasteur.fr", "url": "https://research.pasteur.fr/fr/member/hugues-aschard/", "orcidid": "http://orcid.org/0000-0002-7554-6783", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Hanna Julienne", "email": "hanna.julienne@pasteur.fr", "url": "https://research.pasteur.fr/fr/member/hanna-julienne/", "orcidid": "https://orcid.org/0000-0001-8214-9412", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Bogdan Pasaniuc", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-0227-2056", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Huwenbo Shi", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-9886-877X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "hmenager", "additionDate": "2020-01-20T10:07:47Z", "lastUpdate": "2024-11-24T20:59:22.136271Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "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": "WHISCY", "description": "WHISCY is a program to predict protein-protein interfaces. It is primarily based on conservation, but it also takes into account structural information. A sequence alignment is used to calculate a prediction score for each surface residue of your protein.", "homepage": "https://bianca.science.uu.nl/whiscy/", "biotoolsID": "WHISCY", "biotoolsCURIE": "biotools:WHISCY", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_3534", "term": "Protein binding sites" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "BioExcel", "WeNMR", "INSTRUCT", "EGI" ], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Netherlands" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [ { "url": "https://github.com/haddocking/whiscy/releases", "type": "Downloads page", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://github.com/haddocking/whiscy", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1002/prot.20842", "pmid": "16450362", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "WHISCY: What information does surface conservation yield? Application to data-driven docking", "abstract": "Protein-protein interactions play a key role in biological processes. Identifying the interacting residues is a first step toward understanding these interactions at a structural level. In this study, the interface prediction program WHISCY is presented. It combines surface conservation and structural information to predict protein-protein interfaces. The accuracy of the predictions is more than three times higher than a random prediction. These predictions have been combined with another interface prediction program, ProMate [Neuvirth et al. J Mol Biol 2004;338:181-199], resulting in an even more accurate predictor. The usefulness of the predictions was tested using the data-driven docking program HADDOCK [Dominguez et al. J Am Chem Soc 2003;125:1731-1737] in an unbound docking experiment, with the goal of generating as many near-native structures as possible. Unrefined rigid body docking solutions within 10 Å ligand RMSD from the true structure were generated for 22 out of 25 docked complexes. For 18 complexes, more than 100 of the 8000 generated models were correct. Our results demonstrates the potential of using interface predictions to drive protein-protein docking. © 2006 Wiley-Liss, Inc.", "date": "2006-05-15T00:00:00Z", "citationCount": 125, "authors": [ { "name": "De Vries S.J." }, { "name": "Van Dijk A.D.J." }, { "name": "Bonvin A.M.J.J." } ], "journal": "Proteins: Structure, Function and Genetics" } } ], "credit": [ { "name": "Bonvin Lab", "email": "a.m.j.j.bonvin@uu.nl", "url": "http://www.bonvinlab.org", "orcidid": "http://orcid.org/0000-0001-7369-1322", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Provider", "Maintainer", "Developer", "Primary contact" ], "note": null }, { "name": "Utrecht University", "email": null, "url": "https://www.uu.nl", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Netherlands Organization for Scientific Research (NWO), VICI grant no. 700.96.442", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "European H2020 e-Infrastructure grant, EOSC-Hub, grant no.777536", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "a.m.j.j.bonvin@uu.nl", "additionDate": "2019-11-22T12:35:23Z", "lastUpdate": "2024-11-24T15:23:01.942171Z", "editPermission": { "type": "group", "authors": [ "br.jimenezgarcia@gmail.com" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "3D-BioInfo + BioExcel: Protein Conformational Ensembles Generation", "description": "This workflow illustrates the process of generating protein conformational ensembles from 3D structures and analysing its molecular flexibility, step by step, using the BioExcel Building Blocks library (biobb). Workflow included in the ELIXIR 3D-Bioinfo Implementation Study: Building on PDBe-KB to chart and characterize the conformation landscape of native proteins", "homepage": "https://mmb.irbbarcelona.org/biobb/workflows#protein-conformational-ensembles-generation", "biotoolsID": "3d-bioinfo_bioexcel_protein_conformational_ensembles_generation", "biotoolsCURIE": "biotools:3d-bioinfo_bioexcel_protein_conformational_ensembles_generation", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "biobb", "type": "uses" }, { "biotoolsID": "imod", "type": "uses" }, { "biotoolsID": "flexserv", "type": "uses" }, { "biotoolsID": "prody", "type": "uses" }, { "biotoolsID": "nglview", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0474", "term": "Protein structure prediction" }, { "uri": "http://edamontology.org/operation_2406", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/operation_3891", "term": "Essential dynamics" }, { "uri": "http://edamontology.org/operation_3890", "term": "Trajectory visualization" }, { "uri": "http://edamontology.org/operation_0250", "term": "Protein property calculation" }, { "uri": "http://edamontology.org/operation_2939", "term": "Principal component visualisation" } ], "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_3870", "term": "Trajectory data" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" }, { "uri": "http://edamontology.org/format_3874", "term": "PCAzip" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3892", "term": "Biomolecular simulation" }, { "uri": "http://edamontology.org/topic_0081", "term": "Structure analysis" }, { "uri": "http://edamontology.org/topic_3510", "term": "Protein sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0082", "term": "Structure prediction" }, { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [ "BioExcel", "3D-BioInfo", "3D-BioInfo-Protein-Complex" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Interoperability", "Tools" ], "elixirNode": [ "Spain", "Norway", "France", "Belgium", "EMBL", "Hungary", "Denmark" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [ { "url": "https://mmb.irbbarcelona.org/biobb/workflows#protein-conformational-ensembles-generation", "type": [ "Other" ], "note": "Main web site (BioBB workflows)" }, { "url": "https://mmb.irbbarcelona.org/biobb/workflows/tutorials/flexdyn", "type": [ "Other" ], "note": "Tutorial in HTML" }, { "url": "https://biobb-wf-flexdyn.readthedocs.io/en/latest/index.html", "type": [ "Other" ], "note": "Tutorial in Read The Docs" }, { "url": "https://github.com/bioexcel/biobb_wf_flexdyn", "type": [ "Repository" ], "note": "Source Code in GitHub" } ], "download": [ { "url": "https://github.com/bioexcel/biobb_wf_flexdyn", "type": "Source code", "note": null, "version": "1.0" }, { "url": "https://bioexcel-binder.tsi.ebi.ac.uk/v2/gh/bioexcel/biobb_wf_md_setup/master?filepath=biobb_wf_md_setup%2Fnotebooks%2Fbiobb_MDsetup_tutorial.ipynb", "type": "VM image", "note": "BioExcel Binder", "version": "1.0" } ], "documentation": [ { "url": "https://biobb-wf-flexdyn.readthedocs.io/en/latest/?badge=latest", "type": [ "Other" ], "note": "Read The Docs Workflow Documentation" } ], "publication": [ { "doi": "10.1038/s41597-019-0177-4", "pmid": "31506435", "pmcid": "PMC6736963", "type": [ "Other" ], "version": null, "note": "BioExcel Building Blocks (BioBB)", "metadata": { "title": "BioExcel Building Blocks, a software library for interoperable biomolecular simulation workflows", "abstract": "In the recent years, the improvement of software and hardware performance has made biomolecular simulations a mature tool for the study of biological processes. Simulation length and the size and complexity of the analyzed systems make simulations both complementary and compatible with other bioinformatics disciplines. However, the characteristics of the software packages used for simulation have prevented the adoption of the technologies accepted in other bioinformatics fields like automated deployment systems, workflow orchestration, or the use of software containers. We present here a comprehensive exercise to bring biomolecular simulations to the “bioinformatics way of working”. The exercise has led to the development of the BioExcel Building Blocks (BioBB) library. BioBB’s are built as Python wrappers to provide an interoperable architecture. BioBB’s have been integrated in a chain of usual software management tools to generate data ontologies, documentation, installation packages, software containers and ways of integration with workflow managers, that make them usable in most computational environments.", "date": "2019-12-01T00:00:00Z", "citationCount": 39, "authors": [ { "name": "Andrio P." }, { "name": "Hospital A." }, { "name": "Conejero J." }, { "name": "Jorda L." }, { "name": "Del Pino M." }, { "name": "Codo L." }, { "name": "Soiland-Reyes S." }, { "name": "Goble C." }, { "name": "Lezzi D." }, { "name": "Badia R.M." }, { "name": "Orozco M." }, { "name": "Gelpi J.L." } ], "journal": "Scientific Data" } }, { "doi": "10.12688/f1000research.20559.1", "pmid": "32566135", "pmcid": "PMC7284151", "type": [ "Other" ], "version": null, "note": "3D-BioInfo, ELIXIR Structural Community", "metadata": { "title": "A community proposal to integrate structural bioinformatics activities in ELIXIR (3D-Bioinfo Community)", "abstract": "Structural bioinformatics provides the scientific methods and tools to analyse, archive, validate, and present the biomolecular structure data generated by the structural biology community. It also provides an important link with the genomics community, as structural bioinformaticians also use the extensive sequence data to predict protein structures and their functional sites. A very broad and active community of structural bioinformaticians exists across Europe, and 3D-Bioinfo will establish formal platforms to address their needs and better integrate their activities and initiatives. Our mission will be to strengthen the ties with the structural biology research communities in Europe covering life sciences, as well as chemistry and physics and to bridge the gap between these researchers in order to fully realize the potential of structural bioinformatics. Our Community will also undertake dedicated educational, training and outreach efforts to facilitate this, bringing new insights and thus facilitating the development of much needed innovative applications e.g. for human health, drug and protein design. Our combined efforts will be of critical importance to keep the European research efforts competitive in this respect. Here we highlight the major European contributions to the field of structural bioinformatics, the most pressing challenges remaining and how Europe-wide interactions, enabled by ELIXIR and its platforms, will help in addressing these challenges and in coordinating structural bioinformatics resources across Europe. In particular, we present recent activities and future plans to consolidate an ELIXIR 3D-Bioinfo Community in structural bioinformatics and propose means to develop better links across the community. These include building new consortia, organising workshops to establish data standards and seeking community agreement on benchmark data sets and strategies. We also highlight existing and planned collaborations with other ELIXIR Communities and other European infrastructures, such as the structural biology community supported by Instruct-ERIC, with whom we have synergies and overlapping common interests.", "date": "2020-01-01T00:00:00Z", "citationCount": 10, "authors": [ { "name": "Orengo C." }, { "name": "Velankar S." }, { "name": "Wodak S." }, { "name": "Zoete V." }, { "name": "Bonvin A.M.J.J." }, { "name": "Elofsson A." }, { "name": "Feenstra K.A." }, { "name": "Gerloff D.L." }, { "name": "Hamelryck T." }, { "name": "Hancock J.M." }, { "name": "Helmer-Citterich M." }, { "name": "Hospital A." }, { "name": "Orozco M." }, { "name": "Perrakis A." }, { "name": "Rarey M." }, { "name": "Soares C." }, { "name": "Sussman J.L." }, { "name": "Thornton J.M." }, { "name": "Tuffery P." }, { "name": "Tusnady G." }, { "name": "Wierenga R." }, { "name": "Salminen T." }, { "name": "Schneider B." } ], "journal": "F1000Research" } } ], "credit": [ { "name": "Adam Hospital", "email": "adam.hospital@irbbarcelona.org", "url": "https://www.irbbarcelona.org/en/research/adam-hospital", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Documentor", "Maintainer" ], "note": null }, { "name": "Genís Bayarri", "email": "genis.bayarri@irbbarcelona.org", "url": "https://www.irbbarcelona.org/en/research/genis-bayarri", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Maintainer" ], "note": null }, { "name": "3D-BioInfo", "email": "katharina.heil@elixir-europe.org", "url": "https://elixir-europe.org/communities/3d-bioinfo", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Provider" ], "note": null } ], "owner": "adam.hospital@irbbarcelona.org", "additionDate": "2023-05-25T11:54:30.874289Z", "lastUpdate": "2024-11-24T14:47:40.290064Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "SuchTree", "description": "A Python library for doing fast, thread-safe computations with phylogenetic trees.", "homepage": "https://github.com/ryneches/SuchTree", "biotoolsID": "suchtree", "biotoolsCURIE": "biotools:suchtree", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0557", "term": "Phylogenetic tree distances calculation" }, { "uri": "http://edamontology.org/operation_0551", "term": "Phylogenetic tree topology analysis" }, { "uri": "http://edamontology.org/operation_0567", "term": "Phylogenetic tree visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3271", "term": "Gene tree" }, "format": [ { "uri": "http://edamontology.org/format_1910", "term": "newick" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2082", "term": "Matrix" }, "format": [ { "uri": "http://edamontology.org/format_4003", "term": "NumPy format" } ] } ], "note": null, "cmd": "SuchTree.distances_by_name()" } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0084", "term": "Phylogeny" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/ryneches/SuchTree", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/ryneches/SuchTree/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://pypi.org/project/SuchTree/", "type": "Software package", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://github.com/ryneches/SuchTree#readme", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.21105/joss.00678", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "0.7", "note": null, "metadata": null } ], "credit": [ { "name": "Russell Y. 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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. 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Simulation length and the size and complexity of the analyzed systems make simulations both complementary and compatible with other bioinformatics disciplines. However, the characteristics of the software packages used for simulation have prevented the adoption of the technologies accepted in other bioinformatics fields like automated deployment systems, workflow orchestration, or the use of software containers. We present here a comprehensive exercise to bring biomolecular simulations to the “bioinformatics way of working”. The exercise has led to the development of the BioExcel Building Blocks (BioBB) library. BioBB’s are built as Python wrappers to provide an interoperable architecture. 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The method uses discrete molecular dynamics as engine to sample protein conformational space. A multiple minima Go-like potential energy function is used in combination with several enhancing sampling strategies, such as metadynamics, Maxwell Demon molecular dynamics and essential dynamics. The method, which shows an unprecedented computational efficiency, is able to trace a wide range of known experimental transitions. Contrary to simpler methods our strategy does not introduce distortions in the chemical structure of the protein and is able to reproduce well complex non-linear conformational transitions. The method, called GOdMD, can easily introduce additional restraints to the transition (presence of ligand, known intermediate, known maintained contacts, ...) and is freely distributed to the community through the Spanish National Bioinformatics Institute (http://mmb.irbbarcelona.org/GOdMD).Availability: Freely available on the web at http://mmb.irbbarcelona.org/GOdMD.Contact: or modesto@mmb.pcb.ub.esSupplementary information: Supplementary data are available at Bioinformatics online. © 2013 The Author 2013. Published by Oxford University Press.", "date": "2013-08-15T00:00:00Z", "citationCount": 28, "authors": [ { "name": "Sfriso P." }, { "name": "Hospital A." }, { "name": "Emperador A." }, { "name": "Orozco M." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Adam Hospital Gasch", "email": "adam.hospital@irbbarcelona.org", "url": "https://www.irbbarcelona.org/en/research/adam-hospital", "orcidid": "https://orcid.org/0000-0002-8291-8071", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Documentor", "Maintainer" ], "note": null }, { "name": "Genís Bayarri", "email": "genis.bayarri@irbbarcelona.org", "url": "https://www.irbbarcelona.org/es/research/genis-bayarri", "orcidid": "https://orcid.org/0000-0003-0513-0288", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Developer", "Maintainer" ], "note": null }, { "name": "BioExcel CoE", "email": null, 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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": 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"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": "CoCoNat", "description": "CoCoNat is a novel deep-learning based method for predicting coiled-coil regions, register annotation and oligomenrization state. CoCoNat adopts a sequence encoding based on two state-of-the-art protein language models and a deep-learning architetcure to perform prediction.", "homepage": "https://coconat.biocomp.unibo.it", "biotoolsID": "coconat", "biotoolsCURIE": "biotools:coconat", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0268", "term": "Protein super-secondary structure prediction" } ], "input": [ { "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_0896", "term": "Protein report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0736", "term": "Protein folds and structural domains" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [ "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/BolognaBiocomp/coconat", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://github.com/BolognaBiocomp/coconat", "type": [ "Command-line options" ], "note": null }, { "url": "https://coconat.biocomp.unibo.it/help/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btad495", "pmid": "37540220", "pmcid": "PMC10425188", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "CoCoNat: a novel method based on deep learning for coiled-coil prediction", "abstract": "Motivation: Coiled-coil domains (CCD) are widespread in all organisms and perform several crucial functions. Given their relevance, the computational detection of CCD is very important for protein functional annotation. State-of-the-art prediction methods include the precise identification of CCD boundaries, the annotation of the typical heptad repeat pattern along the coiled-coil helices as well as the prediction of the oligomerization state. Results: In this article, we describe CoCoNat, a novel method for predicting coiled-coil helix boundaries, residue-level register annotation, and oligomerization state. Our method encodes sequences with the combination of two state-of-the-art protein language models and implements a three-step deep learning procedure concatenated with a Grammatical-Restrained Hidden Conditional Random Field for CCD identification and refinement. A final neural network predicts the oligomerization state. When tested on a blind test set routinely adopted, CoCoNat obtains a performance superior to the current state-of-the-art both for residue-level and segment-level CCD. CoCoNat significantly outperforms the most recent state-of-the-art methods on register annotation and prediction of oligomerization states.", "date": "2023-08-01T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Madeo G." }, { "name": "Savojardo C." }, { "name": "Manfredi M." }, { "name": "Martelli P.L." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } }, { "doi": "10.21769/BioProtoc.4935", "pmid": "38405078", "pmcid": "PMC10883893", "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "CoCoNat: A Deep Learning–Based Tool for the Prediction of Coiled-coil Domains in Protein Sequences", "abstract": "Coiled-coil domains (CCDs) are structural motifs observed in proteins in all organisms that perform several crucial functions. The computational identification of CCD segments over a protein sequence is of great importance for its functional characterization. This task can essentially be divided into three separate steps: the detection of segment boundaries, the annotation of the heptad repeat pattern along the segment, and the classification of its oligomerization state. Several methods have been proposed over the years addressing one or more of these predictive steps. In this protocol, we illustrate how to make use of CoCoNat, a novel approach based on protein language models, to characterize CCDs. CoCoNat is, at its release (August 2023), the state of the art for CCD detection. The web server allows users to submit input protein sequences and visualize the predicted domains after a few minutes. Optionally, precomputed segments can be provided to the model, which will predict the oligomerization state for each of them. CoCoNat can be easily integrated into biological pipelines by downloading the standalone version, which provides a single executable script to produce the output.", "date": "2024-02-20T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Manfredi M." }, { "name": "Savojardo C." }, { "name": "Martelli P.L." }, { "name": "Casadio R." } ], "journal": "Bio-protocol" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": null, "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": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "Pier Luigi Martelli", "email": "pierluigi.martelli@unibo.it", "url": null, "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": "2024-01-28T18:03:20.705547Z", "lastUpdate": "2024-11-24T14:10:14.901849Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-ITA-BOLOGNA", "savo" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PlasGO", "description": "PlasGO: a Python library (Linux or Ubuntu only) for predicting cluster-level Gene Ontology (GO) terms of plasmid-encoded proteins.", "homepage": "https://github.com/Orin-beep/PlasGO", "biotoolsID": "plasgo", "biotoolsCURIE": "biotools:plasgo", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/Orin-beep/PlasGO", "type": "Software package", "note": null, "version": "1.0" } ], "documentation": [], "publication": [], "credit": [], "owner": "yongxinji2", "additionDate": "2024-10-24T04:20:54.023066Z", "lastUpdate": "2024-10-24T04:20:54.026192Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "get_MNV", "description": "get_MNV is a tool designed to identify Multi-Nucleotide Variants (MNVs) within the same codon in genomic sequences. 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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": "VIQoR", "description": "VIQoR, is a user-friendly web service for Visually supervised protein Inference and protein Quantification implemented in R. 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"publication": [], "credit": [ { "name": "Genís Bayarri", "email": "genis.bayarri@irbbarcelona.org", "url": "https://www.irbbarcelona.org/en/research/genis-bayarri", "orcidid": "https://orcid.org/0000-0003-0513-0288", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Documentor", "Maintainer" ], "note": "Main developer" }, { "name": "Pau Andrio", "email": "pau.andrio@bsc.es", "url": "https://www.bsc.es/andrio-balado-pau", "orcidid": "https://orcid.org/0000-0003-2116-3880", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Developer" ], "note": "Research Support Engineer in the Barcelona Supercomputing Center." }, { "name": "Adam Hospital", "email": "adam.hospital@irbbarcelona.org", "url": "https://www.irbbarcelona.org/en/research/adam-hospital", "orcidid": "https://orcid.org/0000-0002-8291-8071", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": 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However, accurate estimation of local genetic correlation remains challenging, due to linkage disequilibrium in local genomic regions and sample overlap across studies. We introduce SUPERGNOVA, a statistical framework to estimate local genetic correlations using summary statistics from genome-wide association studies. We demonstrate that SUPERGNOVA outperforms existing methods through simulations and analyses of 30 complex traits. In particular, we show that the positive yet paradoxical genetic correlation between autism spectrum disorder and cognitive performance could be explained by two etiologically distinct genetic signatures with bidirectional local genetic correlations.", "date": "2021-12-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Zhang Y." }, { "name": "Lu Q." }, { "name": "Ye Y." }, { "name": "Huang K." }, { "name": "Liu W." }, { "name": "Wu Y." }, { "name": "Zhong X." }, { "name": "Li B." }, { "name": "Yu Z." }, { "name": "Travers B.G." }, { "name": "Werling D.M." }, { "name": "Li J.J." }, { "name": "Zhao H." } ], "journal": "Genome Biology" } } ], "credit": [ { "name": "Hongyu Zhao", "email": "hongyu.zhao@yale.edu", "url": null, "orcidid": "https://orcid.org/0000-0003-1195-9607", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Yiliang Zhang", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Qiongshi Lu", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Yixuan Ye", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "Jennifer", "additionDate": "2022-01-23T23:00:38.802183Z", "lastUpdate": "2022-01-23T23:00:38.805639Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "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", 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"lastUpdate": "2021-06-11T11:48:55Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "metaXplor", "description": "metaXplor is an interactive viral and microbial metagenomic data manager. It aims at storing large volumes of user-defined sample, sequence and assignment information while providing a user-friendly fine-filtering web-interface. This online GUI also offers means to share datasets with collaborators, BLAST external sequences against them, and confirm assignments by running phylogenetic placement. metaXplor is available as a set of Docker containers that make it simple to deploy on various infrastructures.", "homepage": "https://github.com/SouthGreenPlatform/metaXplor", "biotoolsID": "metaxplor", "biotoolsCURIE": "biotools:metaxplor", "version": [ "1.0-beta" ], "otherID": [ { "value": "RRID:SCR_019025", "type": "rrid", "version": null } ], "relation": [], "function": [], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3071", "term": "Biological databases" } ], "operatingSystem": [ "Linux" ], "language": [], "license": "AGPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/SouthGreenPlatform/metaXplor", "type": [ "Repository" ], "note": null }, { "url": "https://metaxplor.cirad.fr/metaXplor/", "type": [ "Other" ], "note": "Live instance with public data" } ], "download": [ { "url": "https://raw.githubusercontent.com/SouthGreenPlatform/metaXplor/master/docker-compose.yml", "type": "Container file", "note": "This is a docker-compose file which upon execution automatically downloads required images", "version": "1.0-beta" } ], "documentation": [ { "url": "https://metaxplor.cirad.fr/metaXplor/docIndex.jsp", "type": [ "User manual" ], "note": "HTML documentation is embedded in the web application" } ], "publication": [], "credit": [ { "name": "Guilhem Sempéré", "email": "guilhem.sempere@cirad.fr", "url": null, "orcidid": "https://orcid.org/0000-0001-7429-2091", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": null, "email": "metaxplor@cirad.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "guilhems", "additionDate": "2020-09-14T08:41:59Z", "lastUpdate": "2021-04-22T06:15:41Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "MendelIHT.jl", "description": "Implements iterative hard thresholding as a multiple regression model for GWAS. Built-in support for handling PLINK and VCF files, parallel computing, fits a variety of GLM models, and handles group/weighting SNPs.", "homepage": "https://github.com/OpenMendel/MendelIHT.jl", "biotoolsID": "mendeliht.jl", "biotoolsCURIE": "biotools:mendeliht.jl", "version": [], "otherID": [ { "value": "RRID:SCR_018292", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3232", "term": "Gene expression QTL analysis" }, { "uri": "http://edamontology.org/operation_3197", "term": "Genetic variation analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3473", "term": "Data mining" }, { "uri": "http://edamontology.org/topic_3053", "term": "Genetics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Julia" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/OpenMendel/MendelIHT.jl", "type": "API specification", "note": "Start Julia, press ] to enter package manager mode, and type the following (after pkg>):\n\n(v1.0) pkg> add https://github.com/OpenMendel/SnpArrays.jl\n(v1.0) pkg> add https://github.com/OpenMendel/MendelSearch.jl\n(v1.0) pkg> add https://github.com/OpenMendel/MendelBase.jl\n(v1.0) pkg> add https://github.com/OpenMendel/MendelIHT.jl", "version": "Julia 1.0-1.3" } ], "documentation": [ { "url": "https://openmendel.github.io/MendelIHT.jl/latest/", "type": [ "API documentation" ], "note": null } ], "publication": [], "credit": [], "owner": "biona001", "additionDate": "2020-04-12T19:40:33Z", "lastUpdate": "2021-04-22T05:53:16Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "LyoPRONTO", "description": "An Open-Source Lyophilization Process Optimization Tool.\n\nThis work presents a new user-friendly lyophilization simulation and process optimization tool, freely available under the name LyoPRONTO. This tool comprises freezing and primary drying calculators, a design-space generator, and a primary drying optimizer. The freezing calculator performs 0D lumped capacitance modeling to predict the product temperature variation with time which shows reasonably good agreement with experimental measurements. The primary drying calculator performs 1D heat and mass transfer analysis in a vial and predicts the drying time with an average deviation of 3% from experiments. The calculator is also extended to generate a design space over a range of chamber pressures and shelf temperatures to predict the most optimal setpoints for operation.", "homepage": "https://sites.google.com/view/rgdart/Research/lyopronto-lyophilization-processoptimization-tool", "biotoolsID": "LyoPRONTO", "biotoolsCURIE": "biotools:LyoPRONTO", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" }, { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" }, { "uri": "http://edamontology.org/operation_3659", "term": "Regression analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3068", "term": "Literature and language" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://drive.google.com/file/d/12is--VvE1bUGAOoNz_UvjMQ4m-SyIEO5/view", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [], "publication": [ { "doi": "10.1208/S12249-019-1532-7", "pmid": "31673810", "pmcid": "PMC6823652", "type": [], "version": null, "note": null, "metadata": { "title": "LyoPRONTO: an Open-Source Lyophilization Process Optimization Tool", "abstract": "© 2019, The Author(s).This work presents a new user-friendly lyophilization simulation and process optimization tool, freely available under the name LyoPRONTO. This tool comprises freezing and primary drying calculators, a design-space generator, and a primary drying optimizer. The freezing calculator performs 0D lumped capacitance modeling to predict the product temperature variation with time which shows reasonably good agreement with experimental measurements. The primary drying calculator performs 1D heat and mass transfer analysis in a vial and predicts the drying time with an average deviation of 3% from experiments. The calculator is also extended to generate a design space over a range of chamber pressures and shelf temperatures to predict the most optimal setpoints for operation. This optimal setpoint varies with time due to the continuously varying product resistance and is taken into account by the optimizer which provides varying chamber pressure and shelf temperature profiles as a function of time to minimize the primary drying time and thereby, the operational cost. The optimization results in 62% faster primary drying for 5% mannitol and 50% faster primary drying for 5% sucrose solutions when compared with typical cycle conditions. This optimization paves the way for the design of the next generation of lyophilizers which when coupled with accurate sensor networks and control systems can result in self-driving freeze dryers.", "date": "2019-11-01T00:00:00Z", "citationCount": 3, "authors": [ { "name": "Shivkumar G." }, { "name": "Kazarin P.S." }, { "name": "Strongrich A.D." }, { "name": "Alexeenko A.A." } ], "journal": "AAPS PharmSciTech" } } ], "credit": [ { "name": "Alina A. Alexeenko", "email": "alexeenk@purdue.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "Pub2Tools", "additionDate": "2020-01-14T09:28:53Z", "lastUpdate": "2021-01-14T08:24:30Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "VISOR", "description": "Haplotype-aware structural variants simulator for short, long and linked reads", "homepage": "https://github.com/davidebolo1993/VISOR", "biotoolsID": "VISOR", "biotoolsCURIE": "biotools:VISOR", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "tricolor", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" }, { "uri": "http://edamontology.org/operation_2928", "term": "Alignment" }, { "uri": "http://edamontology.org/operation_3208", "term": "Genome visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_2914", "term": "Sequence features metadata" }, "format": [ { "uri": "http://edamontology.org/format_3003", "term": "BED" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" } ] }, { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": "VISOR {HACk, SHORtS, LASeR, XENIA} --help" } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3511", "term": "Nucleic acid sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3175", "term": "DNA structural variation" } ], "operatingSystem": [], "language": [ "Shell", "R", "Python" ], "license": "LGPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "EMBL" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/davidebolo1993/VISOR", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/davidebolo1993/VISOR", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://davidebolo1993.github.io/visordoc/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/BIOINFORMATICS/BTZ719", "pmid": "31589307", "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "VISOR: A versatile haplotype-aware structural variant simulator for short-and long-read sequencing", "abstract": "© 2020 Oxford University Press. All rights reserved.VISOR is a tool for haplotype-specific simulations of simple and complex structural variants (SVs). The method is applicable to haploid, diploid or higher ploidy simulations for bulk or single-cell sequencing data. SVs are implanted into FASTA haplotypes at single-basepair resolution, optionally with nearby single-nucleotide variants. Short or long reads are drawn at random from these haplotypes using standard error profiles. Double-or single-stranded data can be simulated and VISOR supports the generation of haplotype-tagged BAM files. The tool further includes methods to interactively visualize simulated variants in single-stranded data. The versatility of VISOR is unmet by comparable tools and it lays the foundation to simulate haplotype-resolved cancer heterogeneity data in bulk or at single-cell resolution.", "date": "2020-02-15T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Bolognini D." }, { "name": "Sanders A." }, { "name": "Korbel J.O." }, { "name": "Magi A." }, { "name": "Benes V." }, { "name": "Rausch T." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Davide Bolognini", "email": "davidebolognini7@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0002-8735-8093", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer", "Documentor", "Developer" ], "note": null } ], "owner": "davidebolo1993", "additionDate": "2020-01-09T17:53:02Z", "lastUpdate": "2021-01-02T16:12:40Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "RetroPath RL", "description": "RetroPath RL performs bio-retrosynthesis using the Monte Carlo Tree Search Reinforcement Learning approach. It is compatible with mono-component reaction rules from RetroRules.", "homepage": "https://github.com/brsynth/RetroPathRL", "biotoolsID": "retropath_rl", "biotoolsCURIE": "biotools:retropath_rl", "version": [], "otherID": [], "relation": [ { "biotoolsID": "retrorules", "type": "uses" } ], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3398", "term": "Bioengineering" }, { "uri": "http://edamontology.org/topic_3895", "term": "Synthetic biology" }, { "uri": "http://edamontology.org/topic_2258", "term": "Cheminformatics" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/brsynth/RetroPathRL", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/brsynth/RetroPathRL", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [], "publication": [ { "doi": "10.1021/acssynbio.9b00447", "pmid": "31841626", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Reinforcement learning for bioretrosynthesis", "abstract": "© 2019 American Chemical Society.Metabolic engineering aims to produce chemicals of interest from living organisms, to advance toward greener chemistry. Despite efforts, the research and development process is still long and costly, and efficient computational design tools are required to explore the chemical biosynthetic space. Here, we propose to explore the bioretrosynthesis space using an artificial intelligence based approach relying on the Monte Carlo Tree Search reinforcement learning method, guided by chemical similarity. We implement this method in RetroPath RL, an open-source and modular command line tool. We validate it on a golden data set of 20 manually curated experimental pathways as well as on a larger data set of 152 successful metabolic engineering projects. Moreover, we provide a novel feature that suggests potential media supplements to complement the enzymatic synthesis plan.", "date": "2020-01-17T00:00:00Z", "citationCount": 9, "authors": [ { "name": "Koch M." }, { "name": "Duigou T." }, { "name": "Faulon J.-L." } ], "journal": "ACS Synthetic Biology" } } ], "credit": [ { "name": "Mathilde Koch", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-8924-3513", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Thomas Duigou", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-2649-2950", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Jean-Loup Faulon", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-4274-2953", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "tduigou", "additionDate": "2020-05-13T16:10:08Z", "lastUpdate": "2020-06-16T10:55:28Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BioExcel Building Blocks tutorials: Command-line workflows", "description": "This tutorial aims to illustrate the process of building up a command-line workflow using the BioExcel Building Blocks library (biobb). The tutorial is based on the Protein Gromacs MD Setup Jupyter Notebook tutorial.", "homepage": "http://mmb.irbbarcelona.org/biobb/availability/tutorials/command-line", "biotoolsID": "bioexcel_building_blocks_tutorials_command-line_workflows", "biotoolsCURIE": "biotools:bioexcel_building_blocks_tutorials_command-line_workflows", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "biobb", "type": "uses" }, { "biotoolsID": "gromacs", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0477", "term": "Protein modelling" }, { "uri": "http://edamontology.org/operation_2476", "term": "Molecular dynamics" } ], "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_3870", "term": "Trajectory data" }, "format": [ { "uri": "http://edamontology.org/format_3910", "term": "trr" } ] }, { "data": { "uri": "http://edamontology.org/data_3872", "term": "Topology data" }, "format": [ { "uri": "http://edamontology.org/format_3883", "term": "GROMACS itp" }, { "uri": "http://edamontology.org/format_3880", "term": "GROMACS top" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0176", "term": "Molecular dynamics" }, { "uri": "http://edamontology.org/topic_0081", "term": "Structure analysis" }, { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [ "BioExcel" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools", "Interoperability" ], "elixirNode": [ "Spain" ], "elixirCommunity": [], "link": [ { "url": "http://mmb.irbbarcelona.org/biobb/availability/tutorials/command-line", "type": [ "Other" ], "note": "Tutorial in HTML" }, { "url": "https://biobb-wf-command-line.readthedocs.io/en/latest/index.html", "type": [ "Other" ], "note": "Tutorial in Read the Docs" }, { "url": "https://github.com/bioexcel/biobb_wf_command-line", "type": [ "Repository" ], "note": "Tutorial in GitHub" } ], "download": [ { "url": "https://github.com/bioexcel/biobb_wf_command-line", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [ { "url": "https://biobb-wf-command-line.readthedocs.io/en/latest/index.html", "type": [ "Other" ], "note": "Read the Docs workflow documentation" } ], "publication": [ { "doi": "10.1038/s41597-019-0177-4", "pmid": "31506435", "pmcid": "PMC6736963", "type": [ "Other" ], "version": "Beta", "note": null, "metadata": { "title": "BioExcel Building Blocks, a software library for interoperable biomolecular simulation workflows", "abstract": "© 2019, The Author(s).In the recent years, the improvement of software and hardware performance has made biomolecular simulations a mature tool for the study of biological processes. Simulation length and the size and complexity of the analyzed systems make simulations both complementary and compatible with other bioinformatics disciplines. However, the characteristics of the software packages used for simulation have prevented the adoption of the technologies accepted in other bioinformatics fields like automated deployment systems, workflow orchestration, or the use of software containers. We present here a comprehensive exercise to bring biomolecular simulations to the “bioinformatics way of working”. The exercise has led to the development of the BioExcel Building Blocks (BioBB) library. BioBB’s are built as Python wrappers to provide an interoperable architecture. BioBB’s have been integrated in a chain of usual software management tools to generate data ontologies, documentation, installation packages, software containers and ways of integration with workflow managers, that make them usable in most computational environments.", "date": "2019-12-01T00:00:00Z", "citationCount": 4, "authors": [ { "name": "Andrio P." }, { "name": "Hospital A." }, { "name": "Conejero J." }, { "name": "Jorda L." }, { "name": "Del Pino M." }, { "name": "Codo L." }, { "name": "Soiland-Reyes S." }, { "name": "Goble C." }, { "name": "Lezzi D." }, { "name": "Badia R.M." }, { "name": "Orozco M." }, { "name": "Gelpi J.L." } ], "journal": "Scientific Data" } } ], "credit": [ { "name": "Genís Bayarri", "email": "genis.bayarri@irbbarcelona.org", "url": "https://www.irbbarcelona.org/en/profile/genis-bayarri", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Documentor", "Maintainer" ], "note": null }, { "name": "Pau Andrio", "email": "pau.andrio@bsc.es", "url": "https://www.bsc.es/andrio-balado-pau", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Documentor", "Maintainer", "Support" ], "note": null }, { "name": "Adam Hospital", "email": "adam.hospital@irbbarcelona.org", "url": null, "orcidid": "https://orcid.org/0000-0002-8291-8071", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "BioExcel Centre of Excellence", "email": null, "url": "https://bioexcel.eu/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Provider" ], "note": null } ], "owner": "adam.hospital@irbbarcelona.org", "additionDate": "2020-05-28T17:24:03Z", "lastUpdate": "2020-06-16T10:55:28Z", "editPermission": { "type": "group", "authors": [ "gelpi@ub.edu", "aniewielska" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "aqmm", "description": "The AQMM was developed to perform absolute quantification of multiple metagenomes and it's parallel metatranscriptome. In order to use this algorithm, the experiment should be designed with both metagenome and metatranscriptome data. From the initial stage, the molecular experimental data should be recorded to help on estimating the overall DNA or RNA of a unit (ml/gram) of the sample. The AQMM was demonstrated to obtain better results of differential expression genes identification in comparative metatranscriptomic studies.", "homepage": "https://github.com/biofuture/aqmm", "biotoolsID": "aqmm", "biotoolsCURIE": "biotools:aqmm", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2526", "term": "Text data" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2526", "term": "Text data" }, "format": [] } ], "note": "run the estimation", "cmd": "perl ./aqmm -a <Input_metagenome_dir> -b <Input_metatranscriptome_dir> -m <Experimental_meta_data> -n <num_threads> -o <ouput_dir> Author Jiang Xiao-Tao 2017-08 Email biofuture.jiang@gmail.com\nwhere:\n\n-a <Input_metagenome_dir> including all the fq files of your metagenomic samples after quality filtering\n\n-b <Input_metatranscriptome_dir> including all the paralell metatranscriptomic fq files with metagenomic samples after . remvoing the rRNA with tools like SortMeRNA.\n\n-m meta_data.txt including all the experimental extraction information and the extraction efficiency information of your sample type\n\n-o <ouput_dir> will include all the output results for the quantification, including the esimated cell numbers of metagenomic data of each sample and the estimated sequenced cell numbers your metatranscriptomic data included. With the quantification results obtained, the abundance of gene/species could be futher normalized to per cell/volume/gram etc. al." } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" } ], "operatingSystem": [ "Linux" ], "language": [ "Perl" ], "license": "GPL-3.0", "collectionID": [ "metagenome", "metatranscriptome", "absolute quantification" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/biofuture/aqmm", "type": [ "Other" ], "note": "github page" } ], "download": [ { "url": "https://github.com/biofuture/aqmm.git", "type": "Downloads page", "note": "Github repo", "version": "1.0" } ], "documentation": [ { "url": "https://aqmm.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": "readoc document address" } ], "publication": [], "credit": [], "owner": "biofuture", "additionDate": "2020-05-29T01:36:09Z", "lastUpdate": "2020-06-16T10:55:28Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "GREIN", "description": "Interactive Web Platform for Re-analyzing Gene Expression Omnibus (GEO) RNA-seq Data.", "homepage": "https://shiny.ilincs.org/grein", "biotoolsID": "GREIN", "biotoolsCURIE": "biotools:GREIN", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Deposition" }, { "uri": "http://edamontology.org/operation_3223", "term": "Differential gene expression analysis" }, { "uri": "http://edamontology.org/operation_2495", "term": "Expression analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" }, { "uri": "http://edamontology.org/topic_3518", "term": "Microarray experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "R" ], "license": "GPL-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/uc-bd2k/grein", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/uc-bd2k/grein/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://hub.docker.com/r/ucbd2k/grein", "type": "Container file", "note": null, "version": null }, { "url": "https://github.com/uc-bd2k/GREIN/releases/tag/1.0", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [ { "url": "http://www.ilincs.org/apps/grein/?gse=", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/S41598-019-43935-8", "pmid": "31110304", "pmcid": "PMC6527554", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "GREIN: An Interactive Web Platform for Re-analyzing GEO RNA-seq Data", "abstract": "© 2019, The Author(s).The vast amount of RNA-seq data deposited in Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) is still a grossly underutilized resource for biomedical research. To remove technical roadblocks for reusing these data, we have developed a web-application GREIN (GEO RNA-seq Experiments Interactive Navigator) which provides user-friendly interfaces to manipulate and analyze GEO RNA-seq data. GREIN is powered by the back-end computational pipeline for uniform processing of RNA-seq data and the large number (>6,500) of already processed datasets. The front-end user interfaces provide a wealth of user-analytics options including sub-setting and downloading processed data, interactive visualization, statistical power analyses, construction of differential gene expression signatures and their comprehensive functional characterization, and connectivity analysis with LINCS L1000 data. The combination of the massive amount of back-end data and front-end analytics options driven by user-friendly interfaces makes GREIN a unique open-source resource for re-using GEO RNA-seq data. GREIN is accessible at: https://shiny.ilincs.org/grein, the source code at: https://github.com/uc-bd2k/grein, and the Docker container at: https://hub.docker.com/r/ucbd2k/grein.", "date": "2019-12-01T00:00:00Z", "citationCount": 25, "authors": [ { "name": "Mahi N.A." }, { "name": "Najafabadi M.F." }, { "name": "Pilarczyk M." }, { "name": "Kouril M." }, { "name": "Medvedovic M." } ], "journal": "Scientific Reports" } } ], "credit": [ { "name": "Mario Medvedovic", "email": "medvedm@ucmail.uc.edu", "url": null, "orcidid": "https://orcid.org/0000-0003-4510-3102", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "hans", "additionDate": "2019-08-09T13:04:29Z", "lastUpdate": "2020-06-16T10:55:25Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ComplexBrowser", "description": "ComplexBrowser is a R based software for supervised analysis of changes in protein complex abundance and subunit co-expression in proteomic datasets. It uses information contained in CORUM and EBI Complex Portal databases to provide the user with visualizations helping with biological interpretation of obtained results. 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"term": "Biochemistry" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://miolite2.iceht.forth.gr", "type": [ "Other" ], "note": "The download website" } ], "download": [ { "url": "http://miolite2.iceht.forth.gr", "type": "Downloads page", "note": "List is incorporated in the M-IOLITE software but can also be obtained as a separate file upon request.", "version": "1.0" } ], "documentation": [ { "url": "http://miolite2.iceht.forth.gr", "type": [ "General" ], "note": "The website provides information about citing the respective tool and how to contact the developer for obtaining the database." } ], "publication": [ { "doi": "10.1016/j.ifacol.2016.12.140", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Streamlining GC-MS metabolomic analysis using the M-IOLITE software suite", "abstract": "© 2016Metabolomics, as a rapidly growing omic analysis, has being used extensively to explore the dynamic response of biological systems in several diseases/disorders and contexts. Therefore, it has become commonplace in a wide variety of disciplines and there is an intense need for development of software suites that provide the user with a less complicated and invalid analysis. These suites must integrate meta-analysis, a standardized data normalization method and a safe repository for all types of biological samples. In the case of the Gas Chromatography-Mass Spectrometry (GC-MS) metabolomics, due to the complexity of the analysis, multiple procedures that are essential for the metabolite identification require special manipulation. Moreover, metabolomic analysis produces a vast amount of unidentified compound data, so there is a need for unknown peak identification methods. While a number of tools offer access to datasets, constantly providing new releases for data processing and the fact that considerable progress has been made in that area, there is no computational platform that emerges as a standardized approach which includes specialized normalization methods for GC-MS metabolomic analysis and incorporates the metabolic network analysis into data interpretation and unknown peak identification. To address these issues, as the datasets obtained from metabolomics experiments still remain extremely large and dense, we have implemented M-IOLITE, a computational suite for the efficient and automatic analysis of high-throughput metabolomic experiments. The aim of the suite is to streamline GC-MS metabolomic data analysis and to reduce complexity enabling the use of a friendly interface for processing, validating and annotating data. It integrates specialized normalization methods, a safe data repository and a peak library providing through its pipeline a useful tool which enables rapid and accurate analysis of the metabolomic profiles into an interactive system.", "date": "2016-01-01T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Maga-Nteve C." }, { "name": "Klapa M.I." } ], "journal": "IFAC-PapersOnLine" } } ], "credit": [ { "name": "Maria Klapa", "email": "mklapa@iceht.forth.gr", "url": "http://miolite2.iceht.forth.gr", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "mklapa", "additionDate": "2017-09-11T15:08:17Z", "lastUpdate": "2019-07-26T16:58:29Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null } ] }