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{ "count": 503, "next": "?page=2", "previous": null, "list": [ { "name": "PIA - Protein Inference Algorithms", "description": "The main focus lays on the integrated inference algorithms, concluding the proteins from a set of identified spectra. But it also allows you to integrate results of various search engines, inspect your peptide spectrum matches, calculate FDR values across different results and visualize the correspondence between PSMs, peptides and proteins.", "homepage": "https://github.com/medbioinf/pia", "biotoolsID": "pia", "biotoolsCURIE": "biotools:pia", "version": [ "1.5" ], "otherID": [], "relation": [ { "biotoolsID": "knime", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3767", "term": "Protein identification" }, { "uri": "http://edamontology.org/operation_3649", "term": "Target-Decoy" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrometry spectra" }, "format": [ { "uri": "http://edamontology.org/format_3713", "term": "Mascot .dat file" }, { "uri": "http://edamontology.org/format_3247", "term": "mzIdentML" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" }, { "uri": "http://edamontology.org/format_3684", "term": "PRIDE XML" }, { "uri": "http://edamontology.org/format_3711", "term": "X!Tandem XML" }, { "uri": "http://edamontology.org/format_3702", "term": "MSF" }, { "uri": "http://edamontology.org/format_3681", "term": "mzTab" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0945", "term": "Peptide identification" }, "format": [ { "uri": "http://edamontology.org/format_2206", "term": "Sequence feature table format (text)" }, { "uri": "http://edamontology.org/format_3765", "term": "KNIME datatable format" }, { "uri": "http://edamontology.org/format_3764", "term": "idXML" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" }, { "uri": "http://edamontology.org/format_3681", "term": "mzTab" }, { "uri": "http://edamontology.org/format_3247", "term": "mzIdentML" } ] }, { "data": { "uri": "http://edamontology.org/data_0989", "term": "Protein identifier" }, "format": [ { "uri": "http://edamontology.org/format_2206", "term": "Sequence feature table format (text)" }, { "uri": "http://edamontology.org/format_3765", "term": "KNIME datatable format" }, { "uri": "http://edamontology.org/format_3764", "term": "idXML" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" }, { "uri": "http://edamontology.org/format_3681", "term": "mzTab" }, { "uri": "http://edamontology.org/format_3247", "term": "mzIdentML" } ] } ], "note": "PIA allows you to inspect the results of common proteomics spectrum identification search engines, combine them seamlessly and conduct statistical analyses. The main focus of PIA lays on the integrated inference algorithms, i.e. concluding the proteins from a set of identified spectra. But it also allows you to inspect your peptide spectrum matches, calculate FDR values across different search engine results and visualize the correspondence between PSMs, peptides and proteins. Search engine results in several formats peptide spectrum matches (PSMs) and peptides Inferred Proteins", "cmd": null } ], "toolType": [ "Command-line tool", "Library", "Desktop application", "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_3120", "term": "Protein variants" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": "BSD-3-Clause", "collectionID": [ "KNIME", "de.NBI", "Proteomics", "BioInfra.Prot", "CUBiMed.RUB" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "Proteomics" ], "link": [ { "url": "https://github.com/medbioinf/pia", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/mpc-bioinformatics/pia", "type": "Source code", "note": null, "version": null }, { "url": "http://bioconda.github.io/recipes/pia/README.html", "type": "Software package", "note": null, "version": null }, { "url": "https://github.com/mpc-bioinformatics/pia/releases", "type": "Binaries", "note": null, "version": null }, { "url": "https://hub.docker.com/r/julianusz/pia", "type": "Container file", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/medbioinf/pia/wiki", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jproteome.5b00121", "pmid": "25938255", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface", "abstract": "Protein inference connects the peptide spectrum matches (PSMs) obtained from database search engines back to proteins, which are typically at the heart of most proteomics studies. Different search engines yield different PSMs and thus different protein lists. Analysis of results from one or multiple search engines is often hampered by different data exchange formats and lack of convenient and intuitive user interfaces. We present PIA, a flexible software suite for combining PSMs from different search engine runs and turning these into consistent results. PIA can be integrated into proteomics data analysis workflows in several ways. A user-friendly graphical user interface can be run either locally or (e.g., for larger core facilities) from a central server. For automated data processing, stand-alone tools are available. PIA implements several established protein inference algorithms and can combine results from different search engines seamlessly. On several benchmark data sets, we show that PIA can identify a larger number of proteins at the same protein FDR when compared to that using inference based on a single search engine. PIA supports the majority of established search engines and data in the mzIdentML standard format. It is implemented in Java and freely available at https://github.com/mpc-bioinformatics/pia.", "date": "2015-07-02T00:00:00Z", "citationCount": 57, "authors": [ { "name": "Uszkoreit J." }, { "name": "Maerkens A." }, { "name": "Perez-Riverol Y." }, { "name": "Meyer H.E." }, { "name": "Marcus K." }, { "name": "Stephan C." }, { "name": "Kohlbacher O." }, { "name": "Eisenacher M." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1021/acs.jproteome.8b00723", "pmid": "30474983", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Protein Inference Using PIA Workflows and PSI Standard File Formats", "abstract": "Proteomics using LC-MS/MS has become one of the main methods to analyze the proteins in biological samples in high-throughput. But the existing mass-spectrometry instruments are still limited with respect to resolution and measurable mass ranges, which is one of the main reasons why shotgun proteomics is the major approach. Here proteins are digested, which leads to the identification and quantification of peptides instead. While often neglected, the important step of protein inference needs to be conducted to infer from the identified peptides to the actual proteins in the original sample. In this work, we highlight some of the previously published and newly added features of the tool PIA - Protein Inference Algorithms, which helps the user with the protein inference of measured samples. We also highlight the importance of the usage of PSI standard file formats, as PIA is the only current software supporting all available standards used for spectrum identification and protein inference. Additionally, we briefly describe the benefits of working with workflow environments for proteomics analyses and show the new features of the PIA nodes for the KNIME Analytics Platform. Finally, we benchmark PIA against a recently published data set for isoform detection. PIA is open source and available for download on GitHub (https://github.com/mpc-bioinformatics/pia) or directly via the community extensions inside the KNIME analytics platform.", "date": "2019-02-01T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Uszkoreit J." }, { "name": "Perez-Riverol Y." }, { "name": "Eggers B." }, { "name": "Marcus K." }, { "name": "Eisenacher M." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Julian Uszkoreit", "email": "julian.uszkoreit@rub.de", "url": null, "orcidid": "http://orcid.org/0000-0001-7522-4007", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "CUBiMed.RUB", "email": "cubimed@rub.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "julianu", "additionDate": "2016-07-12T10:54:05Z", "lastUpdate": "2025-05-02T13:15:26.717477Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "StripePy", "description": "StripePy recognizes architectural stripes in 3C and Hi-C contact maps using geometric reasoning", "homepage": "https://github.com/paulsengroup/StripePy", "biotoolsID": "stripepy", "biotoolsCURIE": "biotools:stripepy", "version": [ "0.0.1", "0.0.2", "1.0.0", "1.1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/paulsengroup/StripePy/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/paulsengroup/StripePy/discussions", "type": [ "Discussion forum" ], "note": null }, { "url": "https://github.com/paulsengroup/StripePy.git", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/paulsengroup/StripePy/releases", "type": "Source code", "note": null, "version": null }, { "url": "https://hub.docker.com/r/paulsengroup/stripepy", "type": "Container file", "note": null, "version": null }, { "url": "https://doi.org/10.5281/zenodo.14283921", "type": "Test data", "note": null, "version": null }, { "url": "https://pypi.org/project/stripepy-hic/", "type": "Binaries", "note": null, "version": null }, { "url": "https://anaconda.org/bioconda/stripepy-hic", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/paulsengroup/StripePy/blob/main/README.md", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1101/2024.12.20.629789", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "robomics", "additionDate": "2024-12-21T15:24:55.662209Z", "lastUpdate": "2025-05-02T11:01:00.332596Z", "editPermission": { "type": "group", "authors": [ "rea1991" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "OpenMS", "description": "Open source library and a collection of tools and interfaces for the analysis of mass spectrometry data. Includes over 200 standalone (TOPP) tools that can be combined to a workflow with the integrated workflow editor TOPPAS. 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"https://github.com/OpenMS/OpenMS", "type": "Source code", "note": null, "version": null }, { "url": "http://sourceforge.net/projects/open-ms/files/OpenMS/OpenMS-2.0/", "type": "Binaries", "note": null, "version": null }, { "url": "https://github.com/OpenMS/OpenMS", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "http://ftp.mi.fu-berlin.de/pub/OpenMS/release-documentation/html/index.html", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/nmeth.3959", "pmid": "27575624", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "OpenMS: A flexible open-source software platform for mass spectrometry data analysis", "abstract": "© 2016 Nature America, Inc. All rights reserved.High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.", "date": "2016-08-30T00:00:00Z", "citationCount": 246, "authors": [ { "name": "Rost H.L." }, { "name": "Sachsenberg T." }, { "name": "Aiche S." }, { "name": "Bielow C." }, { "name": "Weisser H." }, { "name": "Aicheler F." }, { "name": "Andreotti S." }, { "name": "Ehrlich H.-C." }, { "name": "Gutenbrunner P." }, { "name": "Kenar E." }, { "name": "Liang X." }, { "name": "Nahnsen S." }, { "name": "Nilse L." }, { "name": "Pfeuffer J." }, { "name": "Rosenberger G." }, { "name": "Rurik M." }, { "name": "Schmitt U." }, { "name": "Veit J." }, { "name": "Walzer M." }, { "name": "Wojnar D." }, { "name": "Wolski W.E." }, { "name": "Schilling O." }, { "name": "Choudhary J.S." }, { "name": "Malmstrom L." }, { "name": "Aebersold R." }, { "name": "Reinert K." }, { "name": "Kohlbacher O." } ], "journal": "Nature Methods" } }, { "doi": "10.1007/978-1-60761-987-1_23", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "OpenMS and TOPP: open source software for LC-MS data analysis.", "abstract": "Proteomics experiments based on state-of-the-art mass spectrometry produce vast amounts of data, which cannot be analyzed manually. Hence, software is needed which is able to analyze the data in an automated fashion. The need for robust and reusable software tools triggered the development of libraries implementing different algorithms for the various analysis steps. OpenMS is such a software library and provides a wealth of data structures and algorithms for the analysis of mass spectrometric data. For users unfamiliar with programming, TOPP (\"The OpenMS Proteomics Pipeline\") offers a wide range of already implemented tools sharing the same interface and designed for a specific analysis task each. TOPP thus makes the sophisticated algorithms of OpenMS accessible to nonprogrammers. The individual TOPP tools can be strung together into pipelines for analyzing mass spectrometry-based experiments starting from the raw output of the mass spectrometer. These analysis pipelines can be constructed using a graphical editor. Even complex analytical workflows can thus be analyzed with ease.", "date": "2011-01-01T00:00:00Z", "citationCount": 65, "authors": [ { "name": "Bertsch A." }, { "name": "Gropl C." }, { "name": "Reinert K." }, { "name": "Kohlbacher O." } ], "journal": "Methods in molecular biology (Clifton, N.J.)" } } ], "credit": [ { "name": "ETH Zürich", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Eberhard-Karls-Universität Tübingen", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Freie Universität Berlin", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Center for Integrative Bioinformatics (CiBi)", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [], "note": null }, { "name": "cibi", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "General Mailinglist", "email": "open-ms-general@lists.sourceforge.net", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Support" ], "note": null }, { "name": "General Mailinglist", "email": "open-ms-general@lists.sourceforge.net", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Hannes Röst", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0003-0990-7488", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "samwein", "additionDate": "2016-01-19T16:39:56Z", "lastUpdate": "2025-04-30T11:39:30.251890Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "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": "hictkpy", "description": "Python bindings for hictk: read and write .cool and .hic files directly from Python", "homepage": "https://github.com/paulsengroup/hictkpy", "biotoolsID": "hictkpy", "biotoolsCURIE": "biotools:hictkpy", "version": [ "0.0.1", "0.0.2", "0.0.3", "0.0.4", "0.0.5", "1.0.0", "1.1.0", "1.2.0" ], "otherID": [], "relation": [ { "biotoolsID": "hictk", "type": "uses" } ], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/paulsengroup/hictkpy", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/paulsengroup/hictkpy/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/paulsengroup/hictkpy/discussions", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://github.com/paulsengroup/hictkpy/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://pypi.org/project/hictkpy/", "type": "Binaries", "note": null, "version": null }, { "url": "https://anaconda.org/bioconda/hictkpy", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://hictkpy.readthedocs.io/en/stable/", "type": [ "General" ], "note": null }, { "url": "https://hictkpy.readthedocs.io/en/stable/installation.html", "type": [ "Installation instructions" ], "note": null }, { "url": "https://hictkpy.readthedocs.io/en/stable/quickstart.html", "type": [ "Quick start guide" ], "note": null }, { "url": "https://hictkpy.readthedocs.io/en/stable/api/index.html", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btae408", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "hictk: blazing fast toolkit to work with. hic and. cool files", "abstract": "Motivation: Hi-C is gaining prominence as a method for mapping genome organization. With declining sequencing costs and a growing demand for higher-resolution data, efficient tools for processing Hi-C datasets at different resolutions are crucial. Over the past decade, the. hic and Cooler file formats have become the de-facto standard to store interaction matrices produced by Hi-C experiments in binary format. Interoperability issues make it unnecessarily difficult to convert between the two formats and to develop applications that can process each format natively. Results: We developed hictk, a toolkit that can transparently operate on. hic and. cool files with excellent performance. The toolkit is written in C++ and consists of a C++ library with Python and R bindings as well as CLI tools to perform common operations directly from the shell, including converting between. hic and. mcool formats. We benchmark the performance of hictk and compare it with other popular tools and libraries. We conclude that hictk significantly outperforms existing tools while providing the flexibility of natively working with both file formats without code duplication.", "date": "2024-07-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Rossini R." }, { "name": "Paulsen J." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "robomics", "additionDate": "2024-04-18T08:31:46.459964Z", "lastUpdate": "2025-04-14T22:54:26.266145Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "hictk", "description": "Blazing fast toolkit to work with .hic and .cool files", "homepage": "https://github.com/paulsengroup/hictk", "biotoolsID": "hictk", "biotoolsCURIE": "biotools:hictk", "version": [ "0.0.1", "0.0.2", "0.0.3", "0.0.4", "0.0.5", "0.0.6", "0.0.7", "0.0.8", "0.0.9", "0.0.10", "0.0.11", "0.0.12", "1.0.0", "2.0.0", "2.0.1", "2.0.2", "2.1.0", "2.1.1" ], "otherID": [], "relation": [ { "biotoolsID": "hictkpy", "type": "usedBy" }, { "biotoolsID": "hictkr", "type": "usedBy" } ], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/paulsengroup/hictk", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/paulsengroup/hictk/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/paulsengroup/hictk/discussions", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://github.com/paulsengroup/hictk/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://anaconda.org/bioconda/hictk", "type": "Binaries", "note": null, "version": null }, { "url": "https://github.com/paulsengroup/hictk/pkgs/container/hictk", "type": "Container file", "note": null, "version": null } ], "documentation": [ { "url": "https://hictk.readthedocs.io/en/stable/index.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btae408", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "hictk: blazing fast toolkit to work with. hic and. cool files", "abstract": "Motivation: Hi-C is gaining prominence as a method for mapping genome organization. With declining sequencing costs and a growing demand for higher-resolution data, efficient tools for processing Hi-C datasets at different resolutions are crucial. Over the past decade, the. hic and Cooler file formats have become the de-facto standard to store interaction matrices produced by Hi-C experiments in binary format. Interoperability issues make it unnecessarily difficult to convert between the two formats and to develop applications that can process each format natively. Results: We developed hictk, a toolkit that can transparently operate on. hic and. cool files with excellent performance. The toolkit is written in C++ and consists of a C++ library with Python and R bindings as well as CLI tools to perform common operations directly from the shell, including converting between. hic and. mcool formats. We benchmark the performance of hictk and compare it with other popular tools and libraries. We conclude that hictk significantly outperforms existing tools while providing the flexibility of natively working with both file formats without code duplication.", "date": "2024-07-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Rossini R." }, { "name": "Paulsen J." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "robomics", "additionDate": "2024-02-02T14:42:46.030561Z", "lastUpdate": "2025-04-14T22:54:16.319235Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "COPASI", "description": "Open-source software application for creating and solving mathematical models of biological processes such as metabolic networks, cell-signaling pathways, regulatory networks, infectious diseases, and many others. It includes features to define models of biological processes, simulate and analyze these models, generate analysis reports, and import/export models in SBML format.", "homepage": "http://copasi.org/", "biotoolsID": "copasi", "biotoolsCURIE": "biotools:copasi", "version": [], "otherID": [], "relation": [ { "biotoolsID": "corc", "type": "usedBy" }, { "biotoolsID": "pycotools", "type": "usedBy" }, { "biotoolsID": "biosimulations", "type": "includedIn" }, { "biotoolsID": "sbmlwebapp", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3562", "term": "Network simulation" }, { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" }, { "uri": "http://edamontology.org/operation_3660", "term": "Metabolic network modelling" }, { "uri": "http://edamontology.org/operation_3926", "term": "Pathway visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2600", "term": "Pathway or network" }, "format": [ { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_3239", "term": "CopasiML" }, { "uri": "http://edamontology.org/format_3685", "term": "SED-ML" }, { "uri": "http://edamontology.org/format_3686", "term": "COMBINE OMEX" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2600", "term": "Pathway or network" }, "format": [ { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_3239", "term": "CopasiML" }, { "uri": "http://edamontology.org/format_3685", "term": "SED-ML" }, { "uri": "http://edamontology.org/format_3686", "term": "COMBINE OMEX" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++" ], "license": "Artistic-2.0", "collectionID": [ "de.NBI", "EBI Training Tools" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://groups.google.com/g/copasi-user-forum", "type": [ "Discussion forum" ], "note": "User Forum" }, { "url": "http://tracker.copasi.org/", "type": [ "Issue tracker" ], "note": "Issue tracker" }, { "url": "https://github.com/copasi/COPASI", "type": [ "Repository" ], "note": "Github Repo" }, { "url": "https://fosstodon.org/@copasi", "type": [ "Social media" ], "note": null } ], "download": [ { "url": "http://copasi.org/Download/", "type": "Binaries", "note": "Source and binary packages are available for download.", "version": null } ], "documentation": [ { "url": "http://copasi.org/Support/User_Manual/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btl485", "pmid": "17032683", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "COPASI - A COmplex PAthway SImulator", "abstract": "Motivation: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods. Results: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic-stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation. © 2006 Oxford University Press.", "date": "2006-12-15T00:00:00Z", "citationCount": 1960, "authors": [ { "name": "Hoops S." }, { "name": "Gauges R." }, { "name": "Lee C." }, { "name": "Pahle J." }, { "name": "Simus N." }, { "name": "Singhal M." }, { "name": "Xu L." }, { "name": "Mendes P." }, { "name": "Kummer U." } ], "journal": "Bioinformatics" } }, { "doi": "10.1007/978-1-59745-525-1_2", "pmid": "19399433", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Computational modeling of biochemical networks using COPASI", "abstract": "Computational modeling and simulation of biochemical networks is at the core of systems biology and this includes many types of analyses that can aid understanding of how these systems work. COPASI is a generic software package for modeling and simulation of biochemical networks which provides many of these analyses in convenient ways that do not require the user to program or to have deep knowledge of the numerical algorithms. Here we provide a description of how these modeling techniques can be applied to biochemical models using COPASI. The focus is both on practical aspects of software usage as well as on the utility of these analyses in aiding biological understanding. Practical examples are described for steady-state and time-course simulations, stoichiometric analyses, parameter scanning, sensitivity analysis (including metabolic control analysis), global optimization, parameter estimation, and stochastic simulation. The examples used are all published models that are available in the BioModels database in SBML format. © 2009 Humana Press.", "date": "2009-12-01T00:00:00Z", "citationCount": 168, "authors": [ { "name": "Mendes P." }, { "name": "Hoops S." }, { "name": "Sahle S." }, { "name": "Gauges R." }, { "name": "Dada J." }, { "name": "Kummer U." } ], "journal": "Methods in Molecular Biology" } }, { "doi": "10.1016/j.jbiotec.2017.06.1200", "pmid": "28655634", "pmcid": "PMC5623632", "type": [], "version": null, "note": null, "metadata": { "title": "COPASI and its applications in biotechnology", "abstract": "COPASI is software used for the creation, modification, simulation and computational analysis of kinetic models in various fields. It is open-source, available for all major platforms and provides a user-friendly graphical user interface, but is also controllable via the command line and scripting languages. These are likely reasons for its wide acceptance. We begin this review with a short introduction describing the general approaches and techniques used in computational modeling in the biosciences. Next we introduce the COPASI package, and its capabilities, before looking at typical applications of COPASI in biotechnology.", "date": "2017-11-10T00:00:00Z", "citationCount": 75, "authors": [ { "name": "Bergmann F.T." }, { "name": "Hoops S." }, { "name": "Klahn B." }, { "name": "Kummer U." }, { "name": "Mendes P." }, { "name": "Pahle J." }, { "name": "Sahle S." } ], "journal": "Journal of Biotechnology" } } ], "credit": [ { "name": null, "email": null, "url": "http://copasi.org/About/Team/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Frank T. 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"name": "ATAC Primer Tool (APT)", "description": "A tool for designing primers and identifying accurate normalization controls for ATAC-qPCR.", "homepage": "https://github.com/ChangLab/ATACPrimerTool", "biotoolsID": "apt", "biotoolsCURIE": "biotools:apt", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2419", "term": "Primer and probe design" }, { "uri": "http://edamontology.org/operation_2480", "term": "Structure analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3003", "term": "BED" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_1317", "term": "Structural biology" }, { "uri": "http://edamontology.org/topic_3295", "term": "Epigenetics" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" } ], "operatingSystem": [], "language": [ "R", "Perl" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/ChangLab/ATACPrimerTool", "type": "Binaries", "note": null, "version": null }, { "url": "https://github.com/ChangLab/ATACPrimerTool/blob/master/Running_APT_with_Galaxy.md", "type": "Tool wrapper (Galaxy)", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/ChangLab/ATACPrimerTool", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/nmeth.4663", "pmid": "29702633", "pmcid": "PMC5942889", "type": [], "version": null, "note": null, "metadata": { "title": "ATAC Primer Tool for targeted analysis of accessible chromatin", "abstract": "", "date": "2018-04-27T00:00:00Z", "citationCount": 12, "authors": [ { "name": "Yost K.E." }, { "name": "Carter A.C." }, { "name": "Xu J." }, { "name": "Litzenburger U." }, { "name": "Chang H.Y." } ], "journal": "Nature Methods" } } ], "credit": [ { "name": "Howard Y Chang", "email": "howchang@stanford.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-EE", "additionDate": "2018-05-15T18:39:04Z", "lastUpdate": "2024-11-25T14:49:42.942234Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MAMBO", "description": "MAMBO (Metabolomic Analysis of Metagenomes using fBa and Optimization) is an algorithm which assesses and optimizes correlations between genome-scale, constraint-based metabolic models and microbial abundance profiles obtained from shotgun sequence data.", "homepage": "https://github.com/danielriosgarza/MAMBO", "biotoolsID": "mambo", "biotoolsCURIE": "biotools:mambo", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3465", "term": "Correlation" }, { "uri": "http://edamontology.org/operation_0226", "term": "Annotation" }, { "uri": "http://edamontology.org/operation_3562", "term": "Network simulation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3736", "term": "Ecological data" }, "format": [ { "uri": "http://edamontology.org/format_3706", "term": "Biodiversity data format" } ] }, { "data": { "uri": "http://edamontology.org/data_2093", "term": "Data reference" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3617", "term": "Graph format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_3473", "term": "Data mining" } ], "operatingSystem": [], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/danielriosgarza/MAMBO", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/danielriosgarza/MAMBO", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/s41564-018-0124-8", "pmid": "29531366", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Towards predicting the environmental metabolome from metagenomics with a mechanistic model", "abstract": "The environmental metabolome and metabolic potential of microorganisms are dominant and essential factors shaping microbial community composition. Recent advances in genome annotation and systems biology now allow us to semiautomatically reconstruct genome-scale metabolic models (GSMMs) of microorganisms based on their genome sequence 1 . Next, growth of these models in a defined metabolic environment can be predicted in silico, mechanistically linking the metabolic fluxes of individual microbial populations to the community dynamics. A major advantage of GSMMs is that no training data is needed, besides information about the metabolic capacity of individual genes (genome annotation) and knowledge of the available environmental metabolites that allow the microorganism to grow. However, the composition of the environment is often not fully determined and remains difficult to measure 2 . We hypothesized that the relative abundance of different bacterial species, as measured by metagenomics, can be combined with GSMMs of individual bacteria to reveal the metabolic status of a given biome. Using a newly developed algorithm involving over 1,500 GSMMs of human-associated bacteria, we inferred distinct metabolomes for four human body sites that are consistent with experimental data. Together, we link the metagenome to the metabolome in a mechanistic framework towards predictive microbiome modelling.", "date": "2018-04-01T00:00:00Z", "citationCount": 66, "authors": [ { "name": "Garza D.R." }, { "name": "Van Verk M.C." }, { "name": "Huynen M.A." }, { "name": "Dutilh B.E." } ], "journal": "Nature Microbiology" } } ], "credit": [ { "name": "Bas E. 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It performs targeted automated metabolite identification, isotopologue mass and abundance determination and natural isotope abundance correction.\nAs it is designed to detect metabolites irrespective of the extent of isotopic labelling, this software may also be used to perform targeted analysis on unlabelled data sets.", "homepage": "https://github.com/DExSI/DExSI", "biotoolsID": "dexsi", "biotoolsCURIE": "biotools:dexsi", "version": [ "1.11" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" }, { "uri": "http://edamontology.org/operation_3694", "term": "Mass spectrum visualisation" }, { "uri": "http://edamontology.org/operation_3632", "term": "Isotopic distributions calculation" }, { "uri": "http://edamontology.org/operation_3635", "term": "Labeled quantification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3650", "term": "NetCDF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1636", "term": "Heat map" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3547", "term": "Image format" } ] } ], "note": "DExSI performs automated metabolite annotation, mass and positional isotopomer abundance determination and natural isotope abundance correction. It provides a range of output options and is suitable for high throughput analyses.", "cmd": null } ], "toolType": [ "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" } ], "operatingSystem": [ "Windows" ], "language": [ "Python" ], "license": "Other", "collectionID": [], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/DExSI/DExSI", "type": [ "Repository" ], "note": "DExSI Webpage" } ], "download": [ { "url": "https://github.com/DExSI/DExSI/releases/download/v1.11/DExSI_setup.exe", "type": "Binaries", "note": "Run 'DExSI_setup.exe' with Administrator rights.\nFollow the prompts in the graphical installer. DExSI will install and will be added to the Start menu.", "version": null } ], "documentation": [ { "url": "https://github.com/DExSI/DExSI", "type": [ "General" ], "note": "Help and Sample files are provided in the installation package. A quick-start guide is also supplied (downloadable from: https://github.com/DExSI/DExSI/blob/master/DExSI%20Quick%20Start%20Guide.pdf)" } ], "publication": [ { "doi": "10.1093/bioinformatics/bty025", "pmid": "29360933", "pmcid": "PMC5972663", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "DExSI: A new tool for the rapid quantitation of 13 C-labelled metabolites detected by GC-MS", "abstract": "Stable isotope directed metabolomics is increasingly being used to measure metabolic fluxes in microbial, plant and animal cells. Incorporation of 13 C/ 15 N isotopes into a wide range of metabolites is typically determined using gas chromatography-mass spectrometry (GC/MS) or other hyphenated mass spectrometry approaches. The DExSI (Data Extraction for Stable Isotope-labelled metabolites) pipeline is an interactive graphical software package which can be used to rapidly quantitate isotopologues for a wide variety of metabolites detected by GC/MS. DExSI performs automated metabolite annotation, mass and positional isotopomer abundance determination and natural isotope abundance correction. It provides a range of output options and is suitable for high throughput analyses.", "date": "2018-06-01T00:00:00Z", "citationCount": 33, "authors": [ { "name": "Dagley M.J." }, { "name": "McConville M.J." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Michael Dagley", "email": "Michael.Dagley@unimelb.edu.au", "url": "https://github.com/DExSI/DExSI", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": null, "email": "Michael.Dagley@unimelb.edu.au", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "michael.dagley", "additionDate": "2018-03-08T04:27:50Z", "lastUpdate": "2024-11-25T14:36:18.540342Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "NanoJ-SQUIRREL", "description": "An analytical approach for quantifying image quality in super-resolution microscopy.", "homepage": "https://bitbucket.org/rhenriqueslab/nanoj-squirrel/wiki/Home", "biotoolsID": "nanoj-squirrel", "biotoolsCURIE": "biotools:nanoj-squirrel", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3552", "term": "Microscope image visualisation" }, { "uri": "http://edamontology.org/operation_2428", "term": "Validation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3547", "term": "Image format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3547", "term": "Image format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Plug-in" ], "topic": [ { "uri": "http://edamontology.org/topic_3385", "term": "Light microscopy" }, { "uri": "http://edamontology.org/topic_3572", "term": "Data quality management" } ], "operatingSystem": [], "language": [], "license": "Apache-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://bitbucket.org/rhenriqueslab/nanoj-squirrel/downloads/", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://bitbucket.org/rhenriqueslab/nanoj-squirrel/downloads/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1038/nmeth.4605", "pmid": "29457791", "pmcid": "PMC5884429", "type": [], "version": null, "note": null, "metadata": { "title": "Quantitative mapping and minimization of super-resolution optical imaging artifacts", "abstract": "Super-resolution microscopy depends on steps that can contribute to the formation of image artifacts, leading to misinterpretation of biological information. 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The C API currently supports fast and exhaustive support for parsing GEM .map files and other mapping formats. The Python gem module allows to integrate the GEM Mapper in python scripts and simplifies development of mapping pipelines.\nIn addition to the library functionality, GEM-Tools also provides a command line tool gemtools, that you can use to start the RNASeq pipeline and various other tools, like the indexer and the statistics module.", "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Python", "C" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/gemtools/gemtools", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "http://barnaserver.com/gemtools/releases/GEMTools-static-i3-1.7.1.tar.gz", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/gemtools/gemtools", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/nmeth.2221", "pmid": "23103880", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "The GEM mapper: Fast, accurate and versatile alignment by filtration", "abstract": "Because of ever-increasing throughput requirements of sequencing data, most existing short-read aligners have been designed to focus on speed at the expense of accuracy. The Genome Multitool (GEM) mapper can leverage string matching by filtration to search the alignment space more efficiently, simultaneously delivering precision (performing fully tunable exhaustive searches that return all existing matches, including gapped ones) and speed (being several times faster than comparable state-of-the-art tools). © 2012 Nature America, Inc. All rights reserved.", "date": "2012-12-01T00:00:00Z", "citationCount": 404, "authors": [ { "name": "Marco-Sola S." }, { "name": "Sammeth M." }, { "name": "Guigo R." }, { "name": "Ribeca P." } ], "journal": "Nature Methods" } } ], "credit": [ { "name": "Thasso Griebel", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Emilio Palumbo", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "Santiago Marco-Sola", "email": "santiagomsola@gmail.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Lab Roderic Guigo Group", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "crg.eu", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Emilio Palumbo", "email": "gemtools@googlegroups.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "francisco.camara@crg.eu", "additionDate": "2016-04-22T13:38:28Z", "lastUpdate": "2024-11-25T14:33:34.633048Z", "editPermission": { "type": "group", "authors": [ "smarco" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DiNAMO", "description": "The DiNAMO software implements an exhaustive algorithm to detect over-represented IUPAC motifs in a set of DNA sequences.", "homepage": "https://github.com/bonsai-team/DiNAMO", "biotoolsID": "dinamo", "biotoolsCURIE": "biotools:dinamo", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0238", "term": "Sequence motif discovery" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0160", "term": "Sequence sites, features and motifs" }, { "uri": "http://edamontology.org/topic_3168", "term": "DNA-Seq" }, { "uri": "http://edamontology.org/topic_3169", "term": "ChIP-seq" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/bonsai-team/DiNAMO/releases", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/bonsai-team/DiNAMO/blob/master/README.md", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1186/s12859-018-2215-1", "pmid": "29890948", "pmcid": "PMC5996464", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "DiNAMO: Highly sensitive DNA motif discovery in high-throughput sequencing data", "abstract": "Background: Discovering over-represented approximate motifs in DNA sequences is an essential part of bioinformatics. This topic has been studied extensively because of the increasing number of potential applications. However, it remains a difficult challenge, especially with the huge quantity of data generated by high throughput sequencing technologies. To overcome this problem, existing tools use greedy algorithms and probabilistic approaches to find motifs in reasonable time. Nevertheless these approaches lack sensitivity and have difficulties coping with rare and subtle motifs. Results: We developed DiNAMO (for DNA MOtif), a new software based on an exhaustive and efficient algorithm for IUPAC motif discovery. We evaluated DiNAMO on synthetic and real datasets with two different applications, namely ChIP-seq peaks and Systematic Sequencing Error analysis. DiNAMO proves to compare favorably with other existing methods and is robust to noise. Conclusions: We shown that DiNAMO software can serve as a tool to search for degenerate motifs in an exact manner using IUPAC models. DiNAMO can be used in scanning mode with sliding windows or in fixed position mode, which makes it suitable for numerous potential applications. Availability:https://github.com/bonsai-team/DiNAMO.", "date": "2018-06-11T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Saad C." }, { "name": "Noe L." }, { "name": "Richard H." }, { "name": "Leclerc J." }, { "name": "Buisine M.-P." }, { "name": "Touzet H." }, { "name": "Figeac M." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Chadi Saad", "email": "chadi.saad@univ-lille1.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "shadi.m", "additionDate": "2018-07-30T15:03:57Z", "lastUpdate": "2024-11-25T14:31:44.889611Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "RnBeads", "description": "An R package for comprehensive analysis of DNA methylation data obtained with any experimental protocol that provides single-CpG resolution.", "homepage": "http://rnbeads.mpi-inf.mpg.de/", "biotoolsID": "rnbeads", "biotoolsCURIE": "biotools:rnbeads", "version": [ "2.0.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3204", "term": "Methylation analysis" }, { "uri": "http://edamontology.org/operation_0531", "term": "Heat map generation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2012", "term": "Sequence coordinates" }, "format": [ { "uri": "http://edamontology.org/format_3578", "term": "IDAT" }, { "uri": "http://edamontology.org/format_3003", "term": "BED" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3173", "term": "Epigenomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [ "de.NBI", "HD-Hub", "BioConductor" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "http://bioconductor.org/packages/release/bioc/html/RnBeads.html", "type": "Binaries", "note": null, "version": null }, { "url": "https://quay.io/repository/biocontainers/bioconductor-rnbeads", "type": "Container file", "note": null, "version": null } ], "documentation": [ { "url": "http://rnbeads.mpi-inf.mpg.de/data/RnBeads.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1038/nmeth.3115", "pmid": "25262207", "pmcid": "PMC4216143", "type": [], "version": null, "note": null, "metadata": { "title": "Comprehensive analysis of DNA methylation data with RnBeads", "abstract": "RnBeads is a software tool for large-scale analysis and interpretation of DNA methylation data, providing a user-friendly analysis workflow that yields detailed hypertext reports (http://rnbeads.mpi-inf.mpg.de/). Supported assays include whole-genome bisulfite sequencing, reduced representation bisulfite sequencing, Infinium microarrays and any other protocol that produces high-resolution DNA methylation data. Notable applications of RnBeads include the analysis of epigenome-wide association studies and epigenetic biomarker discovery in cancer cohorts.", "date": "2014-10-30T00:00:00Z", "citationCount": 474, "authors": [ { "name": "Assenov Y." }, { "name": "Muller F." }, { "name": "Lutsik P." }, { "name": "Walter J." }, { "name": "Lengauer T." }, { "name": "Bock C." } ], "journal": "Nature Methods" } } ], "credit": [ { "name": "Yassen Assenov", "email": null, "url": "https://www.dkfz.de/en/tox/staff/Assenov.html", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Fabian Müller", "email": null, "url": "http://www.mpi-inf.mpg.de/~fmueller/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Pavlo Lutsik", "email": null, "url": "https://www.dkfz.de/en/tox/staff/Lutsik.html", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Michael Scherer", "email": null, "url": "http://www.mpi-inf.mpg.de/~mscherer/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Christoph Bock", "email": null, "url": "http://www.christoph-bock.org/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": null, "email": "rnbeads@mpi-inf.mpg.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": null, "email": null, "url": "https://rnbeads.org/index.html", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "hdhub", "additionDate": "2017-05-18T12:21:48Z", "lastUpdate": "2024-11-25T14:31:09.977658Z", "editPermission": { "type": "group", "authors": [ "Karl_JV" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SAPP", "description": "SAPP is a Semantic Annotation Platform with Provenance and is designed on the basis of Semantic Web and is FAIR by design. The platform and corresponding modules allows you to annotate genomes of various qualities with the full chain of provenance. Resulting is a RDF genome data model which you can query and analyse using SPARQL. Various modules are available which allows you to annotate, visualise and export to various formats.", "homepage": "http://sapp.gitlab.io", "biotoolsID": "sapp", "biotoolsCURIE": "biotools:sapp", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0436", "term": "Coding region prediction" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" }, { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" }, { "uri": "http://edamontology.org/operation_2454", "term": "Gene prediction" }, { "uri": "http://edamontology.org/operation_0338", "term": "Sequence database search" }, { "uri": "http://edamontology.org/operation_0233", "term": "Sequence conversion" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [ { "uri": "http://edamontology.org/format_3255", "term": "Turtle" }, { "uri": "http://edamontology.org/format_1936", "term": "GenBank format" }, { "uri": "http://edamontology.org/format_1927", "term": "EMBL format" }, { "uri": "http://edamontology.org/format_2305", "term": "GFF" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [ { "uri": "http://edamontology.org/format_3255", "term": "Turtle" }, { "uri": "http://edamontology.org/format_1936", "term": "GenBank format" }, { "uri": "http://edamontology.org/format_1927", "term": "EMBL format" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_3391", "term": "Omics" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Java" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://sapp.gitlab.io", "type": [ "Other" ], "note": "Documentation" }, { "url": "http://download.systemsbiology.nl/sapp/", "type": [ "Repository" ], "note": null }, { "url": "https://gitlab.com/sapp", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "http://download.systemsbiology.nl/sapp/", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "http://sapp.gitlab.io", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btx767", "pmid": "29186322", "pmcid": "PMC5905645", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "SAPP: Functional genome annotation and analysis through a semantic framework using FAIR principles", "abstract": "Summary To unlock the full potential of genome data and to enhance data interoperability and reusability of genome annotations we have developed SAPP, a Semantic Annotation Platform with Provenance. SAPP is designed as an infrastructure supporting FAIR de novo computational genomics but can also be used to process and analyze existing genome annotations. SAPP automatically predicts, tracks and stores structural and functional annotations and associated dataset- and element-wise provenance in a Linked Data format, thereby enabling information mining and retrieval with Semantic Web technologies. This greatly reduces the administrative burden of handling multiple analysis tools and versions thereof and facilitates multi-level large scale comparative analysis.", "date": "2018-04-15T00:00:00Z", "citationCount": 32, "authors": [ { "name": "Koehorst J.J." }, { "name": "Van Dam J.C.J." }, { "name": "Saccenti E." }, { "name": "Martins Dos Santos V.A.P." }, { "name": "Suarez-Diez M." }, { "name": "Schaap P.J." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Jasper Koehorst", "email": "jasper.koehorst@wur.nl", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "jjkoehorst", "additionDate": "2018-01-12T10:34:19Z", "lastUpdate": "2024-11-25T14:27:20.721769Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Segway", "description": "Novel method for analyzing multiple tracks of functional genomics data which uses a dynamic Bayesian network (DBN) model, which enables it to analyze the entire genome at 1-bp resolution even in the face of heterogeneous patterns of missing data. This method is the first application of DBN techniques to genome-scale data and the first genomic segmentation method designed for use with the maximum resolution data available from ChIP-seq experiments without downsampling.", "homepage": "http://segway.hoffmanlab.org/", "biotoolsID": "segway", "biotoolsCURIE": "biotools:segway", "version": [ "1.4.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3432", "term": "Clustering" }, { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3108", "term": "Experimental measurement" }, "format": [ { "uri": "http://edamontology.org/format_2919", "term": "Sequence annotation track format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3002", "term": "Annotation track" }, "format": [ { "uri": "http://edamontology.org/format_3003", "term": "BED" } ] }, { "data": { "uri": "http://edamontology.org/data_3002", "term": "Annotation track" }, "format": [ { "uri": "http://edamontology.org/format_2919", "term": "Sequence annotation track format" } ] } ], "note": "Semi-automated genome annotation from functional genomics data Genomedata archive semi-automated genome annotation or segmentation semi-automated genome annotation or segmentation", "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0085", "term": "Functional genomics" }, { "uri": "http://edamontology.org/topic_3173", "term": "Epigenomics" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "GPL-2.0", "collectionID": [ "Segway Suite" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://bitbucket.org/hoffmanlab/segway/", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://bitbucket.org/hoffmanlab/segway/src", "type": "Source code", "note": null, "version": null }, { "url": "https://www.pmgenomics.ca/hoffmanlab/proj/segway/src/segway-1.4.tar.gz", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://bitbucket.org/hoffmanlab/segway/", "type": [ "Terms of use" ], "note": null }, { "url": "http://segway.hoffmanlab.org/", "type": [ "Citation instructions" ], "note": null }, { "url": "http://segway.readthedocs.io/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/nmeth.1937", "pmid": "22426492", "pmcid": "PMC3340533", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Unsupervised pattern discovery in human chromatin structure through genomic segmentation", "abstract": "We trained Segway, a dynamic Bayesian network method, simultaneously on chromatin data from multiple experiments, including positions of histone modifications, transcription-factor binding and open chromatin, all derived from a human chronic myeloid leukemia cell line. In an unsupervised fashion, we identified patterns associated with transcription start sites, gene ends, enhancers, transcriptional regulator CTCF-binding regions and repressed regions. Software and genome browser tracks are at http://noble.gs.washington.edu/proj/ segway/. © 2012 Nature America, Inc. All rights reserved.", "date": "2012-05-01T00:00:00Z", "citationCount": 423, "authors": [ { "name": "Hoffman M.M." }, { "name": "Buske O.J." }, { "name": "Wang J." }, { "name": "Weng Z." }, { "name": "Bilmes J.A." }, { "name": "Noble W.S." } ], "journal": "Nature Methods" } }, { "doi": "10.1093/nar/gks1284", "pmid": "23221638", "pmcid": "PMC3553955", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Integrative annotation of chromatin elements from ENCODE data", "abstract": "The ENCODE Project has generated a wealth of experimental information mapping diverse chromatin properties in several human cell lines. Although each such data track is independently informative toward the annotation of regulatory elements, their interrelations contain much richer information for the systematic annotation of regulatory elements. To uncover these interrelations and to generate an interpretable summary of the massive datasets of the ENCODE Project, we apply unsupervised learning methodologies, converting dozens of chromatin datasets into discrete annotation maps of regulatory regions and other chromatin elements across the human genome. These methods rediscover and summarize diverse aspects of chromatin architecture, elucidate the interplay between chromatin activity and RNA transcription, and reveal that a large proportion of the genome lies in a quiescent state, even across multiple cell types. The resulting annotation of non-coding regulatory elements correlate strongly with mammalian evolutionary constraint, and provide an unbiased approach for evaluating metrics of evolutionary constraint in human. Lastly, we use the regulatory annotations to revisit previously uncharacterized disease-associated loci, resulting in focused, testable hypotheses through the lens of the chromatin landscape. © 2012 The Author(s).", "date": "2013-01-01T00:00:00Z", "citationCount": 376, "authors": [ { "name": "Hoffman M.M." }, { "name": "Ernst J." }, { "name": "Wilder S.P." }, { "name": "Kundaje A." }, { "name": "Harris R.S." }, { "name": "Libbrecht M." }, { "name": "Giardine B." }, { "name": "Ellenbogen P.M." }, { "name": "Bilmes J.A." }, { "name": "Birney E." }, { "name": "Hardison R.C." }, { "name": "Dunham I." }, { "name": "Kellis M." }, { "name": "Noble W.S." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Michael M. Hoffman", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0002-4517-1562", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Eric Roberts", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Princess Margaret Cancer Centre", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "University of Toronto", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": null, "url": "http://segway.hoffmanlab.org/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "michaelhoffman", "additionDate": "2016-09-12T14:02:21Z", "lastUpdate": "2024-11-25T14:24:38.193767Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "CoNet", "description": "Tool that detects significant non-random patterns of co-occurrence (copresence and mutual exclusion) in incidence and abundance data.", "homepage": "http://www.raeslab.org/software/conet.html", "biotoolsID": "conet", "biotoolsCURIE": "biotools:conet", "version": [ "1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3439", "term": "Pathway or network prediction" } ], "input": [], "output": [], "note": "CoNet is a similarity-based network inference tool.", "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": null, "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://psbweb05.psb.ugent.be/conet/documents/CoNetDoc.pdf", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "http://psbweb05.psb.ugent.be/conet/documents/CoNetDoc.pdf", "type": "Source code", "note": null, "version": null }, { "url": "http://psbweb05.psb.ugent.be/conet/documents/CoNetDoc.pdf", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "http://psbweb05.psb.ugent.be/conet/documentation.php", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1371/journal.pcbi.1002606", "pmid": "22807668", "pmcid": "PMC3395616", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Microbial co-occurrence relationships in the Human Microbiome", "abstract": "The healthy microbiota show remarkable variability within and among individuals. In addition to external exposures, ecological relationships (both oppositional and symbiotic) between microbial inhabitants are important contributors to this variation. It is thus of interest to assess what relationships might exist among microbes and determine their underlying reasons. The initial Human Microbiome Project (HMP) cohort, comprising 239 individuals and 18 different microbial habitats, provides an unprecedented resource to detect, catalog, and analyze such relationships. Here, we applied an ensemble method based on multiple similarity measures in combination with generalized boosted linear models (GBLMs) to taxonomic marker (16S rRNA gene) profiles of this cohort, resulting in a global network of 3,005 significant co-occurrence and co-exclusion relationships between 197 clades occurring throughout the human microbiome. This network revealed strong niche specialization, with most microbial associations occurring within body sites and a number of accompanying inter-body site relationships. Microbial communities within the oropharynx grouped into three distinct habitats, which themselves showed no direct influence on the composition of the gut microbiota. Conversely, niches such as the vagina demonstrated little to no decomposition into region-specific interactions. Diverse mechanisms underlay individual interactions, with some such as the co-exclusion of Porphyromonaceae family members and Streptococcus in the subgingival plaque supported by known biochemical dependencies. These differences varied among broad phylogenetic groups as well, with the Bacilli and Fusobacteria, for example, both enriched for exclusion of taxa from other clades. Comparing phylogenetic versus functional similarities among bacteria, we show that dominant commensal taxa (such as Prevotellaceae and Bacteroides in the gut) often compete, while potential pathogens (e.g. Treponema and Prevotella in the dental plaque) are more likely to co-occur in complementary niches. This approach thus serves to open new opportunities for future targeted mechanistic studies of the microbial ecology of the human microbiome. © 2012 Faust et al.", "date": "2012-01-01T00:00:00Z", "citationCount": 1124, "authors": [ { "name": "Faust K." }, { "name": "Sathirapongsasuti J.F." }, { "name": "Izard J." }, { "name": "Segata N." }, { "name": "Gevers D." }, { "name": "Raes J." }, { "name": "Huttenhower C." } ], "journal": "PLoS Computational Biology" } }, { "doi": "10.1038/nrmicro2832", "pmid": "22796884", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Microbial interactions: From networks to models", "abstract": "Metagenomics and 16S pyrosequencing have enabled the study of ecosystem structure and dynamics to great depth and accuracy. Co-occurrence and correlation patterns found in these data sets are increasingly used for the prediction of species interactions in environments ranging from the oceans to the human microbiome. In addition, parallelized co-culture assays and combinatorial labelling experiments allow high-throughput discovery of cooperative and competitive relationships between species. In this Review, we describe how these techniques are opening the way towards global ecosystem network prediction and the development of ecosystem-wide dynamic models. © 2012 Macmillan Publishers Limited. All rights reserved.", "date": "2012-08-01T00:00:00Z", "citationCount": 2583, "authors": [ { "name": "Faust K." }, { "name": "Raes J." } ], "journal": "Nature Reviews Microbiology" } } ], "credit": [ { "name": "Karoline Faust", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Gipsi Lima-Mendez", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "Jean-Sebastien Lerat", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "VUB", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "KU Leuven", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "VIB", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "vib-kuleuven.be", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Karoline Faust", "email": "karoline.faust@vib-kuleuven.be", "url": "http://www.raeslab.org", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Support" ], "note": null }, { "name": "Karoline Faust", "email": "karoline.faust@vib-kuleuven.be", "url": "http://www.raeslab.org", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "karoline.faust@vib-kuleuven.be", "additionDate": "2015-05-20T11:32:54Z", "lastUpdate": "2024-11-25T14:24:14.199125Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "seqcluster", "description": "Analysis of small RNA sequencing data. It detect unit of transcription over the genome, annotate them and create an HTML interactive report that helps to explore the data quickly.", "homepage": "http://seqcluster.readthedocs.org", "biotoolsID": "seqcluster", "biotoolsCURIE": "biotools:seqcluster", "version": [ "1.1.14" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Sequence alignment (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" } ] }, { "data": { "uri": "http://edamontology.org/data_1381", "term": "Sequence alignment (pair)" }, "format": [ { "uri": "http://edamontology.org/format_2572", "term": "BAM" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3112", "term": "Gene expression matrix" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] } ], "note": "Analysis of small RNA sequencing data. It detect unit of transcription over the genome, annotate them and create an HTML interactive report that helps to explore the data quickly.", "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://github.com/lpantano/seqcluster", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "http://github.com/lpantano/seqcluster#cite", "type": "Source code", "note": null, "version": null }, { "url": "http://github.com/bioconda", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "http://github.com/lpantano/seqcluster#cite", "type": [ "Citation instructions" ], "note": null }, { "url": "http://seqcluster.readthedocs.org", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btv632", "pmid": "26530722", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Specific small-RNA signatures in the amygdala at premotor and motor stages of Parkinson's disease revealed by deep sequencing analysis", "abstract": "Motivation: Most computational tools for small non-coding RNAs (sRNA) sequencing data analysis focus in microRNAs (miRNAs), overlooking other types of sRNAs that show multi-mapping hits. Here, we have developed a pipeline to non-redundantly quantify all types of sRNAs, and extract patterns of expression in biologically defined groups. We have used our tool to characterize and profile sRNAs in post-mortem brain samples of control individuals and Parkinson's disease (PD) cases at early-premotor and late-symptomatic stages. Results: Clusters of co-expressed sRNAs mapping onto tRNAs significantly separated premotor and motor cases from controls. A similar result was obtained using a matrix of miRNAs slightly varying in sequence (isomiRs). The present framework revealed sRNA alterations at premotor stages of PD, which might reflect initial pathogenic perturbations. This tool may be useful to discover sRNA expression patterns linked to different biological conditions.", "date": "2016-03-01T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Pantano L." }, { "name": "Friedlander M.R." }, { "name": "Escaramis G." }, { "name": "Lizano E." }, { "name": "Pallares-Albanell J." }, { "name": "Ferrer I." }, { "name": "Estivill X." }, { "name": "Marti E." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bioinformatics/btr527", "pmid": "21976421", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "A non-biased framework for the annotation and classification of the non-mirna small RNA transcriptome", "abstract": "Motivation: Recent progress in high-throughput sequencing technologies has largely contributed to reveal a highly complex landscape of small non-coding RNAs (sRNAs), including novel non-canonical sRNAs derived from long non-coding RNA, repeated elements, transcription start sites and splicing site regions among others. The published frameworks for sRNA data analysis are focused on miRNA detection and prediction, ignoring further information in the dataset. As a consequence, tools for the identification and classification of the sRNAs not belonging to miRNA family are currently lacking. Results: Here, we present, SeqCluster, an extension of the currently available SeqBuster tool to identify and analyze at different levels the sRNAs not annotated or predicted as miRNAs. This new module deals with sequences mapping onto multiple locations and permits a highly versatile and user-friendly interaction with the data in order to easily classify sRNA sequences with a putative functional importance. We were able to detect all known classes of sRNAs described to date using SeqCluster with different sRNA datasets. © The Author 2011. Published by Oxford University Press. All rights reserved.", "date": "2011-11-01T00:00:00Z", "citationCount": 42, "authors": [ { "name": "Pantano L." }, { "name": "Estivill X." }, { "name": "Marti E." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Francisco Pantano Rubino", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Judith Flo Gaya", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Harvard Chan School", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Center of Genomic Regulation", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "hsph.harvard.edu", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "lpantano@iscb.org", "url": "http://github.com/lpantano", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "lpantano@hsph.harvard.edu", "additionDate": "2016-03-17T15:30:36Z", "lastUpdate": "2024-11-25T14:23:47.909735Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null } ] }
