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{ "count": 19290, "next": "?page=2", "previous": null, "list": [ { "name": "fermo-core", "description": "fermo-core is the backend of the metabolomics dashboard FERMO. 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Zdouc", "email": "zdoucmm@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0001-6534-6609", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "Initiator and lead developer" }, { "name": "Fermo Metabolomics", "email": null, "url": "https://github.com/fermo-metabolomics", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Project", "typeRole": [ "Maintainer" ], "note": "Governing body overseeing development" } ], "owner": "mmzdouc", "additionDate": "2025-05-09T18:02:39.924632Z", "lastUpdate": "2025-05-09T18:14:33.071182Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "EUCAIM ETL toolset", "description": "Modular toolchain for an extensible and customizable ETL pipeline that extracts, transforms, and loads clinical data and medical imaging metadata, applying dataset-specific mappings to generate outputs compatible with the EUCAIM Common Data Model (CDM). Its design aims to minimize manual data preparation efforts and facilitate customization and integration with other components, such as data quality assurance tools.\nContainerized, currently supports input datasets in CSV, JSON, XLSX.", "homepage": "https://bahiasoftware.es/home", "biotoolsID": "eetl_toolset", "biotoolsCURIE": "biotools:eetl_toolset", "version": [ "0.9.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0335", "term": "Data formatting" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Data deposition" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0336", "term": "Format validation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Workflow", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3345", "term": "Data identity and mapping" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" } ], "operatingSystem": [ "Linux", "Windows" ], "language": [ "Java", "Python" ], "license": "Apache-2.0", "collectionID": [ "EUCAIM" ], "maturity": "Emerging", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "victorsp", "additionDate": "2025-04-24T13:00:12.867477Z", "lastUpdate": "2025-05-08T09:29:42.363560Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "AMICI", "description": "AMICI provides a multi-language (Python, C++, Matlab) interface for the SUNDIALS solvers CVODES (for ordinary differential equations) and IDAS (for algebraic differential equations). AMICI allows the user to read differential equation models specified as SBML or PySB and automatically compiles such models into .mex simulation files (Matlab), C++ executables or Python modules.\n\nBeyond forward integration, the compiled simulation file also allows for forward sensitivity analysis, steady state sensitivity analysis and adjoint sensitivity analysis for likelihood-based output functions.\n\nThe interface was designed to provide routines for efficient gradient computation in parameter estimation of biochemical reaction models but it is also applicable to a wider range of differential equation constrained optimization problems.", "homepage": "https://github.com/AMICI-dev/AMICI", "biotoolsID": "AMICI", "biotoolsCURIE": "biotools:AMICI", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3562", "term": "Network simulation" }, { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "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_4015", "term": "PEtab" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3870", "term": "Trajectory data" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "MATLAB", "C++", "Python" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/AMICI-dev/AMICI/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://amici.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btab227", "pmid": "33821950", "pmcid": "PMC8545331", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "AMICI: high-performance sensitivity analysis for large ordinary differential equation models", "abstract": "Ordinary differential equation models facilitate the understanding of cellular signal transduction and other biological processes. However, for large and comprehensive models, the computational cost of simulating or calibrating can be limiting. AMICI is a modular toolbox implemented in C++/Python/MATLAB that provides efficient simulation and sensitivity analysis routines tailored for scalable, gradient-based parameter estimation and uncertainty quantification.", "date": "2021-10-15T00:00:00Z", "citationCount": 37, "authors": [ { "name": "Frohlich F." }, { "name": "Weindl D." }, { "name": "Schalte Y." }, { "name": "Pathirana D." }, { "name": "Paszkowski L." }, { "name": "Lines G.T." }, { "name": "Stapor P." }, { "name": "Hasenauer J." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Fabian Fröhlich", "email": "fabian_froehlich@hms.harvard.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer", "Developer" ], "note": null }, { "name": "Jan Hasenauer", "email": "jan.hasenauer@uni-bonn.de", "url": null, "orcidid": "https://orcid.org/0000-0002-4935-3312", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Daniel Weindl", "email": "daniel.weindl@uni-bonn.de", "url": null, "orcidid": "https://orcid.org/0000-0001-9963-6057", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer", "Developer" ], "note": null } ], "owner": "dweindl", "additionDate": "2019-09-28T12:06:10Z", "lastUpdate": "2025-05-08T07:28:52.817175Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "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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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": "pyOpenMS", "description": "Python library for mass spectrometry, specifically for the analysis of proteomics and metabolomics data.", "homepage": "https://github.com/OpenMS/pyopenms-extra/blob/master/docs/source/index.rst", "biotoolsID": "pyOpenMS", "biotoolsCURIE": "biotools:pyOpenMS", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0601", "term": "Protein modifications" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/OpenMS/pyopenms-extra", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/OpenMS/pyopenms-extra/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://pyopenms.readthedocs.io", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.7287/PEERJ.PREPRINTS.27736", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Hannes L. 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It applies the desired changes to the dataset and generates a report containing information about the selected sequences, corrupted files, missing files and merged files.\n\nStatus : Containerized", "homepage": "https://harbor.eucaim.cancerimage.eu/harbor/projects/3/repositories/dicom_file_integrity_checker/artifacts-tab", "biotoolsID": "dicom_file_integrity_checker_by_gibi230", "biotoolsCURIE": "biotools:dicom_file_integrity_checker_by_gibi230", "version": [ "1.2.9", "2.0.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3316", "term": "Computer science" }, { "uri": "http://edamontology.org/topic_3077", "term": "Data acquisition" }, { "uri": "http://edamontology.org/topic_3071", "term": "Data management" } ], "operatingSystem": [ "Linux", "Windows" ], "language": [ "Python" ], "license": null, "collectionID": [ "EUCAIM" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.linkedin.com/company/grupo-de-investigaci%C3%B3n-biom%C3%A9dica-en-imagen/", "type": [ "Social media" ], "note": null } ], "download": [], "documentation": [ { "url": "https://drive.google.com/file/d/1s8-nVAvSuAGTHWwun4AQcgHtRWclsFg2/view?usp=sharing", "type": [ "General" ], "note": "Pedro-Miguel Martinez-Girones 1,*, Adrian Galiana-Bordera 1, Carina Soler-Pons 1, Ignacio Gomez-Rico-Junquero 1, Ignacio Blanquer-Espert 3, Leonor Cerda-Alberich 1 and Luis Marti-Bonmati 1,2\n1\tBiomedical Imaging Research Group (GIBI230), La Fe Health Research Institute (IIS La Fe), Avenida Fernando Abril Martorell, València, 46026, Spain.\n2\tLa Fe Medical Imaging Department, Avenida Fernando Abril Martorell, València, 46026, Spain.\n3\tComputing Science Department, Universitat Politècnica de València, Cami de Vera s/n, València, 46022, Spain." } ], "publication": [], "credit": [ { "name": "GIBI230 - HULAFE", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "pedromiguel_martinez_HULAFE", "additionDate": "2025-04-15T17:42:40.968987Z", "lastUpdate": "2025-04-29T14:29:57.293088Z", "editPermission": { "type": "group", "authors": [ "casopon" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "GO enrichment analysis tool", "description": "A tool for GO term enrichment analysis.", "homepage": "http://geneontology.org/page/go-enrichment-analysis", "biotoolsID": "go_enrichment_tool", "biotoolsCURIE": "biotools:go_enrichment_tool", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3501", "term": "Enrichment analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0077", "term": "Nucleic acids" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "GO Tools" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://geneontology.org/page/go-enrichment-analysis", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/75556", "pmid": "10802651", "pmcid": "PMC3037419", "type": [], "version": null, "note": null, "metadata": null }, { "doi": "10.1093/nar/gku1179", "pmid": "25428369", "pmcid": "PMC4383973", "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": null, "email": null, "url": "http://geneontology.org/form/contact-go", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "training_go_import", "additionDate": "2017-01-17T15:08:16Z", "lastUpdate": "2025-04-29T13:02:02.508664Z", "editPermission": { "type": "group", "authors": [ "Taufik" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Trace4MedicalImageCleaning", "description": "Trace4MedicalImageCleaning™ is a tool aimed at automatically detecting and removing text in medical images, with a specific focus on 2D ultrasound and mammography studies.", "homepage": "http://deeptracetech.com/", "biotoolsID": "trace4medicalimagecleaning", "biotoolsCURIE": "biotools:trace4medicalimagecleaning", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [], "operatingSystem": [ "Windows", "Linux" ], "language": [ "MATLAB", "Python" ], "license": "Proprietary", "collectionID": [ "EUCAIM" ], "maturity": "Emerging", "cost": "Commercial", "accessibility": "Restricted access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "christian.salvatore", "additionDate": "2024-11-18T14:47:41.753481Z", "lastUpdate": "2025-04-29T10:39:22.111602Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MetExplore", "description": "Metabolic network curation, visualisation and omics data analysis. It is possible to curate and annotate metabolic networks in a collaborative environment. Several tools are available for metabolomics data mapping in networks and visualisation.", "homepage": "http://www.metexplore.fr/", "biotoolsID": "metexplore", "biotoolsCURIE": "biotools:metexplore", "version": [ "2.40" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2497", "term": "Pathway or network analysis" }, { "uri": "http://edamontology.org/operation_3083", "term": "Pathway or network visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2600", "term": "Pathway or network" }, "format": [ { "uri": "http://edamontology.org/format_2585", "term": "SBML" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2600", "term": "Pathway or network" }, "format": [ { "uri": "http://edamontology.org/format_3620", "term": "xlsx" }, { "uri": "http://edamontology.org/format_3822", "term": "GML" }, { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_3603", "term": "PNG" }, { "uri": "http://edamontology.org/format_3579", "term": "JPG" }, { "uri": "http://edamontology.org/format_3604", "term": "SVG" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0277", "term": "Pathway or network comparison" }, { "uri": "http://edamontology.org/operation_3083", "term": "Pathway or network visualisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web service", "Workbench" ], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "elixir-fr-sdp-2019", "EBI Training Tools" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://metexplore.toulouse.inra.fr/metexplore-doc/index.php", "type": [ "User manual" ], "note": "User documentation on MetExplore main features." }, { "url": "https://metexplore.toulouse.inra.fr/metexploreViz/doc/documentation.php", "type": [ "User manual" ], "note": "MetExploreViz (metabolic network visualsiation) documentation." }, { "url": "https://metexplore.toulouse.inra.fr/metexplore-webservice-documentation/", "type": [ "API documentation" ], "note": "MetExplore webservice documentation" }, { "url": "https://metexplore.pages.mia.inra.fr/metexplore-training/", "type": [ "Training material" ], "note": "How to use MetExplore to map metabolomics data onto metabolic networks." } ], "publication": [ { "doi": "10.1093/nar/gky301", "pmid": "29718355", "pmcid": "PMC6030842", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "MetExplore: Collaborative edition and exploration of metabolic networks", "abstract": "Metabolism of an organism is composed of hundreds to thousands of interconnected biochemical reactions responding to environmental or genetic constraints. This metabolic network provides a rich knowledge to contextualize omics data and to elaborate hypotheses on metabolic modulations. Nevertheless, performing this kind of integrative analysis is challenging for end users with not sufficiently advanced computer skills since it requires the use of various tools and web servers. MetExplore offers an all-in-one online solution composed of interactive tools for metabolic network curation, network exploration and omics data analysis. In particular, it is possible to curate and annotate metabolic networks in a collaborative environment. The network exploration is also facilitated in MetExplore by a system of interactive tables connected to a powerful network visualization module. Finally, the contextualization of metabolic elements in the network and the calculation of over-representation statistics make it possible to interpret any kind of omics data.", "date": "2018-07-02T00:00:00Z", "citationCount": 92, "authors": [ { "name": "Cottret L." }, { "name": "Frainay C." }, { "name": "Chazalviel M." }, { "name": "Cabanettes F." }, { "name": "Gloaguen Y." }, { "name": "Camenen E." }, { "name": "Merlet B." }, { "name": "Heux S." }, { "name": "Portais J.-C." }, { "name": "Poupin N." }, { "name": "Vinson F." }, { "name": "Jourdan F." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkq312", "pmid": "20444866", "pmcid": "PMC2896158", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "MetExplore: A web server to link metabolomic experiments and genome-scale metabolic networks", "abstract": "High-throughput metabolomic experiments aim at identifying and ultimately quantifying all metabolites present in biological systems. The metabolites are interconnected through metabolic reactions, generally grouped into metabolic pathways. Classical metabolic maps provide a relational context to help interpret metabolomics experiments and a wide range of tools have been developed to help place metabolites within metabolic pathways. However, the representation of metabolites within separate disconnected pathways overlooks most of the connectivity of the metabolome. By definition, reference pathways cannot integrate novel pathways nor show relationships between metabolites that may be linked by common neighbours without being considered as joint members of a classical biochemical pathway. MetExplore is a web server that offers the possibility to link metabolites identified in untargeted metabolomics experiments within the context of genome-scale reconstructed metabolic networks. The analysis pipeline comprises mapping metabolomics data onto the specific metabolic network of an organism, then applying graph-based methods and advanced visualization tools to enhance data analysis. The MetExplore web server is freely accessible at http://metexplore.toulouse.inra.fr. © The Author(s) 2010. Published by Oxford University Press.", "date": "2010-05-05T00:00:00Z", "citationCount": 144, "authors": [ { "name": "Cottret L." }, { "name": "Wildridge D." }, { "name": "Vinson F." }, { "name": "Barrett M.P." }, { "name": "Charles H." }, { "name": "Sagot M.-F." }, { "name": "Jourdan F." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/btx588", "pmid": "28968733", "pmcid": "PMC5860210", "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "MetExploreViz: Web component for interactive metabolic network visualization", "abstract": "Summary MetExploreViz is an open source web component that can be easily embedded in any web site. It provides features dedicated to the visualization of metabolic networks and pathways and thus offers a flexible solution to analyse omics data in a biochemical context.", "date": "2018-01-15T00:00:00Z", "citationCount": 36, "authors": [ { "name": "Chazalviel M." }, { "name": "Frainay C." }, { "name": "Poupin N." }, { "name": "Vinson F." }, { "name": "Merlet B." }, { "name": "Gloaguen Y." }, { "name": "Cottret L." }, { "name": "Jourdan F." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Fabien JOURDAN", "email": "fabien.jourdan@inra.fr", "url": "https://sites.google.com/site/fabienjourdan/", "orcidid": "https://orcid.org/0000-0001-9401-2894", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": null, "email": "ludovic.cottret@inra.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": null, "email": "metexplore@oulouse.inra.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Support" ], "note": null }, { "name": "MetaboHub", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [], "note": null } ], "owner": "fabienjourdan", "additionDate": "2018-07-09T23:06:59Z", "lastUpdate": "2025-04-28T07:17:11.601858Z", "editPermission": { "type": "group", "authors": [ "lcottret", "Jennifer" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "EUCAIM DICOM Anonymizer", "description": "The EUCAIM DICOM Anonymizer anonymizes a set of DICOM files. It supports both anonymization on a case-by-case scenario, meaning one DICOM Study at a time (single-mode) or on multiple cases concurrently (batch mode). Additionally it hashes and links clinical data.", "homepage": "https://harbor.eucaim.cancerimage.eu/harbor/projects/3/repositories/eucaim-anonymizer/", "biotoolsID": "eucaim_dicom_anonymizer", "biotoolsCURIE": "biotools:eucaim_dicom_anonymizer", "version": [ "0.12.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3283", "term": "Anonymisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3384", "term": "Medical imaging" } ], "operatingSystem": [ "Mac", "Windows", "Linux" ], "language": [ "C++" ], "license": null, "collectionID": [ "EUCAIM" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "vkalokyri", "additionDate": "2025-04-14T16:46:40.806977Z", "lastUpdate": "2025-04-24T13:06:17.802389Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "sylph", "description": "fast and precise species-level metagenomic profiling with ANIs", "homepage": "https://github.com/bluenote-1577/sylph", "biotoolsID": "sylph", "biotoolsCURIE": "biotools:sylph", "version": [ "v0.4.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3751", "term": "DSV" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" } ], "operatingSystem": [ "Linux" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "pauffret", "additionDate": "2023-12-06T15:45:20.587393Z", "lastUpdate": "2025-04-24T09:31:08.371089Z", "editPermission": { "type": "group", "authors": [ "vashokan" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Bracken", "description": "Statistical method that computes the abundance of species in DNA sequences from a metagenomics sample.", "homepage": "https://ccb.jhu.edu/software/bracken/", "biotoolsID": "bracken", "biotoolsCURIE": "biotools:bracken", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" } ], "input": [], "output": [], "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" } ], "operatingSystem": [ "Linux" ], "language": [ "Perl", "Python" ], "license": "GPL-3.0", "collectionID": [ "Animal and Crop Genomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/jenniferlu717/Bracken", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/jenniferlu717/Bracken/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://ccb.jhu.edu/software/bracken/index.shtml?t=manual", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.7717/peerj-cs.104", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Bracken: Estimating species abundance in metagenomics data", "abstract": "Metagenomic experiments attempt to characterize microbial communities using high-throughput DNA sequencing. Identification of the microorganisms in a sample provides information about the genetic profile, population structure, and role of microorganisms within an environment. Until recently, most metagenomics studies focused on high-level characterization at the level of phyla, or alternatively sequenced the 16S ribosomalRNAgene that is present in bacterial species. As the cost of sequencing has fallen, though, metagenomics experiments have increasingly used unbiased shotgun sequencing to capture all the organisms in a sample. This approach requires a method for estimating abundance directly from the raw read data. Here we describe a fast, accurate new method that computes the abundance at the species level using the reads collected in a metagenomics experiment. Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN) uses the taxonomic assignments made by Kraken, a very fast read-level classifier, along with information about the genomes themselves to estimate abundance at the species level, the genus level, or above. We demonstrate that Bracken can produce accurate species- and genus-level abundance estimates even when a sample contains multiple near-identical species.", "date": "2017-01-01T00:00:00Z", "citationCount": 900, "authors": [ { "name": "Lu J." }, { "name": "Breitwieser F.P." }, { "name": "Thielen P." }, { "name": "Salzberg S.L." } ], "journal": "PeerJ Computer Science" } } ], "credit": [ { "name": null, "email": "jlu26@jhmi.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "admin", "additionDate": "2017-08-20T15:17:20Z", "lastUpdate": "2025-04-23T07:43:18.805990Z", "editPermission": { "type": "group", "authors": [ "animalandcropgenomics", "ELIXIR-CZ", "bebatut", "vashokan" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Gemma", "description": "Gemma provides data, experimental design annotations, and differential expression analysis results for thousands of microarray and RNA-seq experiments. We re-analyze raw data from public sources (primarily NCBI GEO), annotate experimental conditions, conduct quality control and compute differential expression using standardized procedures. We have especially good coverage of experiments relevant to the nervous system.", "homepage": "https://gemma.msl.ubc.ca/", "biotoolsID": "gemma", "biotoolsCURIE": "biotools:gemma", "version": [ "1.31.13" ], "otherID": [], "relation": [ { "biotoolsID": "rsem", "type": "uses" }, { "biotoolsID": "multiqc", "type": "uses" }, { "biotoolsID": "cutadapt", "type": "uses" }, { "biotoolsID": "star", "type": "uses" }, { "biotoolsID": "ncbi_geo", "type": "uses" }, { "biotoolsID": "sradb", "type": "uses" }, { "biotoolsID": "ncbi_gene", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3223", "term": "Differential gene expression profiling" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3112", "term": "Gene expression matrix" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3110", "term": "Raw microarray data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1636", "term": "Heat map" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3914", "term": "Quality control report" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web API" ], "topic": [ { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_3053", "term": "Genetics" }, { "uri": "http://edamontology.org/topic_3518", "term": "Microarray experiment" }, { "uri": "http://edamontology.org/topic_0219", "term": "Data curation and archival" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java", "JavaScript" ], "license": "CC-BY-NC-4.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/PavlidisLab/Gemma", "type": [ "Repository", "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/PavlidisLab/Gemma/releases", "type": "Downloads page", "note": null, "version": null } ], "documentation": [ { "url": "https://pavlidislab.github.io/Gemma/", "type": [ "General" ], "note": null }, { "url": "https://gemma.msl.ubc.ca/resources/restapidocs/", "type": [ "API documentation" ], "note": "Documentation for the Gemma REST API." } ], "publication": [ { "doi": "10.1093/bioinformatics/btp259", "pmid": "19376825", "pmcid": "PMC2687992", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Application and evaluation of automated semantic annotation of gene expression experiments", "abstract": "Motivation: Many microarray datasets are available online with formalized standards describing the probe sequences and expression values. Unfortunately, the description, conditions and parameters of the experiments are less commonly formalized and often occur as natural language text. This hinders searching, high-throughput analysis, organization and integration of the datasets. Results: We use the lexical resources and software tools from the Unified Medical Language System (UMLS) to extract concepts from text. We then link the UMLS concepts to classes in open biomedical ontologies. The result is accessible and clear semantic annotations of gene expression experiments. We applied the method to 595 expression experiments from Gemma, a resource for re-use and meta-analysis of gene expression profiling data. We evaluated and corrected all stages of the annotation process. The majority of missed annotations were due to a lack of cross-references. The most error-prone stage was the extraction of concepts from phrases. Final review of the annotations in context of the experiments revealed 89% precision. A naive system, lacking the phrase to concept corrections is 68% precise. We have integrated this annotation pipeline into Gemma. © 2009 The Author(s).", "date": "2009-06-09T00:00:00Z", "citationCount": 9, "authors": [ { "name": "French L." }, { "name": "Lane S." }, { "name": "Law T." }, { "name": "Xu L." }, { "name": "Pavlidis P." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/database/baab006", "pmid": "33599246", "pmcid": "PMC7904053", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Curation of over 10 000 transcriptomic studies to enable data reuse", "abstract": "Vast amounts of transcriptomic data reside in public repositories, but effective reuse remains challenging. Issues include unstructured dataset metadata, inconsistent data processing and quality control, and inconsistent probe-gene mappings across microarray technologies. Thus, extensive curation and data reprocessing are necessary prior to any reuse. The Gemma bioinformatics system was created to help address these issues. Gemma consists of a database of curated transcriptomic datasets, analytical software, a web interface and web services. Here we present an update on Gemma's holdings, data processing and analysis pipelines, our curation guidelines, and software features. As of June 2020, Gemma contains 10 811 manually curated datasets (primarily human, mouse and rat), over 395 000 samples and hundreds of curated transcriptomic platforms (both microarray and RNA sequencing). Dataset topics were represented with 10 215 distinct terms from 12 ontologies, for a total of 54 316 topic annotations (mean topics/dataset = 5.2). While Gemma has broad coverage of conditions and tissues, it captures a large majority of available brain-related datasets, accounting for 34% of its holdings. Users can access the curated data and differential expression analyses through the Gemma website, RESTful service and an R package. Database URL: https://gemma.msl.ubc.ca/home.html", "date": "2021-01-01T00:00:00Z", "citationCount": 21, "authors": [ { "name": "Lim N." }, { "name": "Tesar S." }, { "name": "Belmadani M." }, { "name": "Poirier-Morency G." }, { "name": "Mancarci B.O." }, { "name": "Sicherman J." }, { "name": "Jacobson M." }, { "name": "Leong J." }, { "name": "Tan P." }, { "name": "Pavlidis P." } ], "journal": "Database" } } ], "credit": [ { "name": "Pavlidis Lab Support", "email": "pavlab-support@msl.ubc.ca", "url": "https://pavlab.msl.ubc.ca/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Support" ], "note": null } ], "owner": "artrymix", "additionDate": "2017-04-22T17:35:18Z", "lastUpdate": "2025-04-22T22:09:03.811075Z", "editPermission": { "type": "group", "authors": [ "artrymix", "paulpavlidis" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MetaPhlAn", "description": "Computational tool for profiling the composition of microbial communities from metagenomic shotgun sequencing data.", "homepage": "http://segatalab.cibio.unitn.it/tools/metaphlan/index.html", "biotoolsID": "metaphlan", "biotoolsCURIE": "biotools:metaphlan", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" }, { "uri": "http://edamontology.org/format_2573", "term": "SAM" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3751", "term": "DSV" } ] } ], "note": null, "cmd": "metaphlan <fastq_input> --input_type fastq -o <output>" }, { "operation": [ { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3751", "term": "DSV" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3751", "term": "DSV" } ] } ], "note": "Convert SGB-based profile to GTDB taxonomy", "cmd": "sgb_to_gtdb_profile.py -i <metaphlan_output> -o <gtdb_metaphlan_output>" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_0194", "term": "Phylogenomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "MIT", "collectionID": [ "Animal and Crop Genomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/biobakery/MetaPhlAn", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/nmeth.2066", "pmid": "22688413", "pmcid": "PMC3443552", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Metagenomic microbial community profiling using unique clade-specific marker genes", "abstract": "Metagenomic shotgun sequencing data can identify microbes populating a microbial community and their proportions, but existing taxonomic profiling methods are inefficient for increasingly large data sets. We present an approach that uses clade-specific marker genes to unambiguously assign reads to microbial clades more accurately and >50Ã-faster than current approaches. We validated our metagenomic phylogenetic analysis tool, MetaPhlAn, on terabases of short reads and provide the largest metagenomic profiling to date of the human gut. It can be accessed at http://huttenhower.sph.harvard.edu/ metaphlan/. © 2012 Nature America, Inc. All rights reserved.", "date": "2012-08-01T00:00:00Z", "citationCount": 1300, "authors": [ { "name": "Segata N." }, { "name": "Waldron L." }, { "name": "Ballarini A." }, { "name": "Narasimhan V." }, { "name": "Jousson O." }, { "name": "Huttenhower C." } ], "journal": "Nature Methods" } } ], "credit": [ { "name": null, "email": null, "url": "https://groups.google.com/forum/#!forum/metaphlan-users", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "admin", "additionDate": "2017-08-20T15:57:59Z", "lastUpdate": "2025-04-22T12:44:24.859435Z", "editPermission": { "type": "group", "authors": [ "animalandcropgenomics", "ELIXIR-CZ", "bebatut", "vashokan" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "samclip", "description": "Filter SAM file for soft and hard clipped alignments", "homepage": "https://github.com/tseemann/samclip", "biotoolsID": "samclip", "biotoolsCURIE": "biotools:samclip", "version": [ "0.4.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3192", "term": "Sequence trimming" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0102", "term": "Mapping" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Perl" ], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/tseemann/samclip", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://anaconda.org/bioconda/samclip", "type": "Software package", "note": null, "version": "0.4.0" } ], "documentation": [ { "url": "https://github.com/tseemann/samclip", "type": [ "General" ], "note": null } ], "publication": [], "credit": [], "owner": "emmcauley", "additionDate": "2025-04-21T21:06:51.624399Z", "lastUpdate": "2025-04-21T21:06:51.626575Z", "editPermission": { "type": "group", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "NetPicoRNA", "description": "Neural network predictions of cleavage sites of picornaviral proteases.", "homepage": "http://cbs.dtu.dk/services/NetPicoRNA/", "biotoolsID": "netpicorna", "biotoolsCURIE": "biotools:netpicorna", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0422", "term": "Protein cleavage site prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1277", "term": "Protein features" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_2955", "term": "Sequence report" }, "format": [ { "uri": "http://edamontology.org/format_2333", "term": "Binary format" } ] } ], "note": "produces neural network predictions of cleavage sites of picornaviral proteases", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3510", "term": "Protein sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0160", "term": "Sequence sites, features and motifs" } ], "operatingSystem": [ "Linux" ], "language": [], "license": "Other", "collectionID": [], "maturity": "Legacy", "cost": "Free of charge (with restrictions)", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://cbs.dtu.dk/services", "type": [ "Software catalogue" ], "note": null } ], "download": [], "documentation": [ { "url": "http://www.cbs.dtu.dk/services/NetPicoRNA/instructions.php", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1002/pro.5560051107", "pmid": "8931139", "pmcid": "PMC2143287", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Cleavage site analysis in picornaviral polyproteins: Discovering cellular targets by neural networks", "abstract": "Picornaviral proteinases are responsible for maturation cleavages of the viral polyprotein, but also catalyze the degradation of cellular targets. Using graphical visualization techniques and neural network algorithms, we have investigated the sequence specificity of the two proteinases 2A(pro) and 3C(pro). The cleavage of VP0 (giving rise to VP2 and VP4), which is carried out by a so-far unknown proteinase, was also examined. In combination with a novel surface exposure prediction algorithm, our neural network approach successfully distinguishes known cleavage sites from noncleavage sites and yields a more consistent definition of features common to these sites. The method is able to predict experimentally determined cleavage sites in cellular proteins. We present a list of mammalian and other proteins that are predicted to be possible targets for the vital proteinases. Whether these proteins are indeed cleaved awaits experimental verification. Additionally, we report several errors detected in the protein databases.", "date": "1996-01-01T00:00:00Z", "citationCount": 204, "authors": [ { "name": "Blom N." }, { "name": "Hansen J." }, { "name": "Blaas D." }, { "name": "Brunak S." } ], "journal": "Protein Science" } } ], "credit": [ { "name": "CBS", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Nikolaj Sorgenfrei Blom", "email": "nikob@cbs.dtu.dk", "url": null, "orcidid": "https://orcid.org/0000-0001-7787-7853", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "powehi", "additionDate": "2015-06-29T10:14:28Z", "lastUpdate": "2025-04-21T12:49:56.070719Z", "editPermission": { "type": "group", "authors": [ "powehi" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SLiM", "description": "Evolutionary simulation framework that combines a powerful engine for population genetic simulations with the capability of modeling arbitrarily complex evolutionary scenarios. Includes a graphical modeling environment.", "homepage": "https://messerlab.org/slim/", "biotoolsID": "SLiM_software", "biotoolsCURIE": "biotools:SLiM_software", "version": [ "5.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0550", "term": "DNA substitution modelling" }, { "uri": "http://edamontology.org/operation_0230", "term": "Sequence generation" }, { "uri": "http://edamontology.org/operation_3946", "term": "Ecological modelling" } ], "input": [], "output": [], "note": "Run individual-based eco-evolutionary simulations with explicit genetics", "cmd": null } ], "toolType": [ "Command-line tool", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0610", "term": "Ecology" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_3299", "term": "Evolutionary biology" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [ "C++" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://messerlab.org/slim/", "type": [ "Software catalogue" ], "note": "SLiM home page in the Messer Lab website" }, { "url": "https://github.com/MesserLab/SLiM", "type": [ "Repository" ], "note": "GitHub repository for SLiM" }, { "url": "https://groups.google.com/g/slim-discuss", "type": [ "Discussion forum" ], "note": "Discussion forum for SLiM questions" }, { "url": "https://groups.google.com/g/slim-announce", "type": [ "Mailing list" ], "note": "Announcements mailing list" } ], "download": [ { "url": "http://benhaller.com/slim/SLiM.zip", "type": "Source code", "note": "A source archive for the command-line `slim` tool only. Complete source code is on GitHub, but most platforms have an installer anyway; see the manual, chapter 2, for installation instructions.", "version": null }, { "url": "https://github.com/MesserLab/SLiM/releases/latest", "type": "Downloads page", "note": "The GitHub page for the current release version, to obtain full source code.", "version": null } ], "documentation": [ { "url": "http://benhaller.com/slim/SLiM_Manual.pdf", "type": [ "User manual" ], "note": "The manual for SLiM itself" }, { "url": "http://benhaller.com/slim/Eidos_Manual.pdf", "type": [ "User manual" ], "note": "The manual for Eidos, the scripting language used by SLiM" }, { "url": "http://benhaller.com/slim/SLiMEidosRefSheets.zip", "type": [ "Quick start guide" ], "note": "Quick reference sheets for SLiM and Eidos" } ], "publication": [ { "doi": "10.1093/molbev/msy228", "pmid": "30517680", "pmcid": "PMC6389312", "type": [ "Other" ], "version": null, "note": "B.C. Haller, P.W. Messer. (2019). SLiM 3: Forward genetic simulations beyond the Wright–Fisher Model. Molecular Biology and Evolution 36(3), 632–637.", "metadata": { "title": "SLiM 3: Forward Genetic Simulations Beyond the Wright-Fisher Model", "abstract": "With the desire to model population genetic processes under increasingly realistic scenarios, forward genetic simulations have become a critical part of the toolbox of modern evolutionary biology. The SLiM forward genetic simulation framework is one of the most powerful and widely used tools in this area. However, its foundation in the Wright-Fisher model has been found to pose an obstacle to implementing many types of models; it is difficult to adapt the Wright-Fisher model, with its many assumptions, to modeling ecologically realistic scenarios such as explicit space, overlapping generations, individual variation in reproduction, density-dependent population regulation, individual variation in dispersal or migration, local extinction and recolonization, mating between subpopulations, age structure, fitness-based survival and hard selection, emergent sex ratios, and so forth. In response to this need, we here introduce SLiM 3, which contains two key advancements aimed at abolishing these limitations. First, the new non-Wright-Fisher or \"nonWF\" model type provides a much more flexible foundation that allows the easy implementation of all of the above scenarios and many more. Second, SLiM 3 adds support for continuous space, including spatial interactions and spatial maps of environmental variables. We provide a conceptual overview of these new features, and present several example models to illustrate their use.", "date": "2019-03-01T00:00:00Z", "citationCount": 504, "authors": [ { "name": "Haller B.C." }, { "name": "Messer P.W." } ], "journal": "Molecular Biology and Evolution" } }, { "doi": "10.1093/molbev/msy237", "pmid": "30590560", "pmcid": "PMC6501880", "type": [ "Usage" ], "version": null, "note": "B.C. Haller, P.W. Messer. (2019). Evolutionary modeling in SLiM 3 for beginners. Molecular Biology and Evolution 36(5), 1101–1109.", "metadata": { "title": "Evolutionary Modeling in SLiM 3 for Beginners", "abstract": "The SLiM forward genetic simulation framework has proved to be a powerful and flexible tool for population genetic modeling. However, as a complex piece of software with many features that allow simulating a diverse assortment of evolutionary models, its initial learning curve can be difficult. Here we provide a step-by-step demonstration of how to build a simple evolutionary model in SLiM 3, to help new users get started. We will begin with a panmictic neutral model, and build up to a model of the evolution of a polygenic quantitative trait under selection for an environmental phenotypic optimum.", "date": "2019-05-01T00:00:00Z", "citationCount": 12, "authors": [ { "name": "Haller B.C." }, { "name": "Messer P.W." } ], "journal": "Molecular Biology and Evolution" } }, { "doi": "10.1111/1755-0998.12968", "pmid": "30565882", "pmcid": "PMC6393187", "type": [ "Method" ], "version": null, "note": "B.C. Haller, J. Galloway, J. Kelleher, P.W. Messer, P.L. Ralph. (2019). Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes. Molecular Ecology Resources 19(2), 552–566.", "metadata": { "title": "Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes", "abstract": "There is an increasing demand for evolutionary models to incorporate relatively realistic dynamics, ranging from selection at many genomic sites to complex demography, population structure, and ecological interactions. Such models can generally be implemented as individual-based forward simulations, but the large computational overhead of these models often makes simulation of whole chromosome sequences in large populations infeasible. This situation presents an important obstacle to the field that requires conceptual advances to overcome. The recently developed tree-sequence recording method (Kelleher, Thornton, Ashander, & Ralph, 2018), which stores the genealogical history of all genomes in the simulated population, could provide such an advance. This method has several benefits: (1) it allows neutral mutations to be omitted entirely from forward-time simulations and added later, thereby dramatically improving computational efficiency; (2) it allows neutral burn-in to be constructed extremely efficiently after the fact, using “recapitation”; (3) it allows direct examination and analysis of the genealogical trees along the genome; and (4) it provides a compact representation of a population's genealogy that can be analysed in Python using the msprime package. We have implemented the tree-sequence recording method in SLiM 3 (a free, open-source evolutionary simulation software package) and extended it to allow the recording of non-neutral mutations, greatly broadening the utility of this method. To demonstrate the versatility and performance of this approach, we showcase several practical applications that would have been beyond the reach of previously existing methods, opening up new horizons for the modelling and exploration of evolutionary processes.", "date": "2019-03-01T00:00:00Z", "citationCount": 109, "authors": [ { "name": "Haller B.C." }, { "name": "Galloway J." }, { "name": "Kelleher J." }, { "name": "Messer P.W." }, { "name": "Ralph P.L." } ], "journal": "Molecular Ecology Resources" } }, { "doi": "10.1086/723601", "pmid": "37130229", "pmcid": "PMC10793872", "type": [ "Primary" ], "version": null, "note": "B.C. Haller, P.W. Messer. (2023). SLiM 4: Multispecies eco-evolutionary modeling. The American Naturalist 201(5), E127–E139.", "metadata": { "title": "SLiM 4: Multispecies Eco-Evolutionary Modeling", "abstract": "The SLiM software framework for genetically explicit forward simulation has been widely used in population genetics. However, it has been largely restricted to modeling only a single species, which has limited its broader utility in evolutionary biology. Indeed, to our knowledge no general-purpose, flexible modeling framework exists that provides support for simulating multiple species while also providing other key features, such as explicit genetics and continuous space. The lack of such software has limited our ability to model higher biological levels such as communities, eco-systems, coevolutionary and eco-evolutionary processes, and bio-diversity, which is crucial for many purposes, from extending our basic understanding of evolutionary ecology to informing conservation and management decisions. We here announce the release of SLiM 4, which fills this important gap by adding support for multiple species, including ecological interactions between species such as predation, parasitism, and mutualism, and illustrate its new features with examples.", "date": "2023-05-01T00:00:00Z", "citationCount": 79, "authors": [ { "name": "Haller B.C." }, { "name": "Messer P.W." } ], "journal": "American Naturalist" } } ], "credit": [ { "name": "Philipp Messer", "email": "messer@cornell.edu", "url": "https://messerlab.org", "orcidid": "https://orcid.org/0000-0001-8453-9377", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Benjamin C. Haller", "email": "bhaller@benhaller.com", "url": "http://benhaller.com", "orcidid": "https://orcid.org/0000-0003-1874-8327", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "bchaller", "additionDate": "2019-05-27T16:59:15Z", "lastUpdate": "2025-04-18T17:40:38.228809Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "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": "openVRE", "description": "The Open Virtual Research Environment is a general purpose analysis platform that can be tailored for domain specific analyses.", "homepage": "https://github.com/inab/openVRE/wiki", "biotoolsID": "openvre", "biotoolsCURIE": "biotools:openvre", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "mugvre", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3760", "term": "Service management" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Bioinformatics portal", "Workbench" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Linux" ], "language": [ "PHP", "Python", "JavaScript" ], "license": "Apache-2.0", "collectionID": [ "EUCAIM" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Spain" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/inab/openVRE", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [ { "url": "http://vre.multiscalegenomics.eu/help/starting.php", "type": [ "Quick start guide" ], "note": "Getting Started Guide" } ], "publication": [], "credit": [ { "name": "Laia Codó", "email": "laia.codo@bsc.es", "url": "https://www.bsc.es/codo-laia", "orcidid": "https://orcid.org/0000-0002-6797-8746", "gridid": "grid.10097.3f", "rorid": "05sd8tv96", "fundrefid": "10.13039/501100006433", "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "Senior Researcher at Barcelona Supercomputing Center. Lead of Trusted Research Environments and Cloud Computing at INB Lab." }, { "name": "Josep Lluís Gelpí", "email": "gelpi@ub.edu", "url": "https://webgrec.ub.edu/webpages/000011/ang/gelpi.ub.edu.html", "orcidid": "http://orcid.org/0000-0002-0566-7723", "gridid": "grid.5841.8", "rorid": "021018s57", "fundrefid": "10.13039/501100005774", "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Professor at University of Barcelona and Team Leader at BSC's INB Laboratory" } ], "owner": "gelpi@ub.edu", "additionDate": "2025-04-16T08:53:57.270825Z", "lastUpdate": "2025-04-16T08:53:57.280528Z", "editPermission": { "type": "group", "authors": [ "gelpi@ub.edu" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "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": "RDMkit", "description": "RDMkit is the Research Data Management toolkit for Life Sciences, providing best practices and guidelines to for FAIR (Findable, Accessible, Interoperable and Reusable) data management.", "homepage": "https://rdmkit.elixir-europe.org", "biotoolsID": "rdmkit", "biotoolsCURIE": "biotools:rdmkit", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Web application" ], "topic": [], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data", "Interoperability", "Training" ], "elixirNode": [ "UK", "Norway", "Belgium", "Germany", "Finland", "Spain" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/elixir-europe/rdmkit", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://zenodo.org/record/5110061", "type": "Downloads page", "note": null, "version": null } ], "documentation": [], "publication": [], "credit": [], "owner": "munazah", "additionDate": "2022-11-03T14:53:22.145643Z", "lastUpdate": "2025-04-11T13:03:16.201584Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PLAZA 4.0", "description": "Integrative resource for functional, evolutionary and comparative plant genomics.\n\nPLAZA is an access point for plant comparative genomics, centralizing genomic data produced by different genome sequencing initiatives.\n\nThis intermediate update of the PLAZA platform, with a focus on the Monocots, became necessary due to substantial annotation updates to species present in the 4.0 PLAZA instances.", "homepage": "https://bioinformatics.psb.ugent.be/plaza", "biotoolsID": "plaza_4.0", "biotoolsCURIE": "biotools:plaza_4.0", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0553", "term": "Gene tree construction" }, { "uri": "http://edamontology.org/operation_0558", "term": "Phylogenetic tree annotation" }, { "uri": "http://edamontology.org/operation_0567", "term": "Phylogenetic tree visualisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" }, { "uri": "http://edamontology.org/topic_0085", "term": "Functional genomics" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": null, "collectionID": [ "BIG N2N", "VIB", "UGent" ], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://bioinformatics.psb.ugent.be/plaza/documentation", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/NAR/GKX1002", "pmid": "29069403", "pmcid": "PMC5753339", "type": [], "version": null, "note": null, "metadata": { "title": "PLAZA 4.0: An integrative resource for functional, evolutionary and comparative plant genomics", "abstract": "PLAZA (https://bioinformatics.psb.ugent.be/plaza) is a plant-oriented online resource for comparative, evolutionary and functional genomics. The PLAZA platform consists of multiple independent instances focusing on different plant clades, while also providing access to a consistent set of reference species. Each PLAZA instance contains structural and functional gene annotations, gene family data and phylogenetic trees and detailed gene colinearity information. A user-friendly web interface makes the necessary tools and visualizations accessible, specific for each data type. Here we present PLAZA 4.0, the latest iteration of the PLAZA framework. This version consists of two new instances (Dicots 4.0 and Monocots 4.0) providing a large increase in newly available species, and offers access to updated and newly implemented tools and visualizations, helping users with the ever-increasing demands for complex and in-depth analyzes. The total number of species across both instances nearly doubles from 37 species in PLAZA 3.0 to 71 species in PLAZA 4.0, with a much broader coverage of crop species (e.g. wheat, palm oil) and species of evolutionary interest (e.g. spruce, Marchantia). The new PLAZA instances can also be accessed by a programming interface through a RESTful web service, thus allowing bioinformaticians to optimally leverage the power of the PLAZA platform.", "date": "2018-01-01T00:00:00Z", "citationCount": 338, "authors": [ { "name": "Van Bel M." }, { "name": "Diels T." }, { "name": "Vancaester E." }, { "name": "Kreft L." }, { "name": "Botzki A." }, { "name": "Van De Peer Y." }, { "name": "Coppens F." }, { "name": "Vandepoele K." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Klaas Vandepoele", "email": "klaas.vandepoele@ugent.vib.be", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "bits@vib.be", "additionDate": "2020-09-03T19:08:44Z", "lastUpdate": "2025-04-11T09:29:36.505334Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "MuDoGeR", "description": "The Multi-Domain Genome Recovery v1.0 (MuDoGeR v1.0) framework is a tool developed to help users to recover Metagenome-Assembled Genomes and Uncultivated Viral Genomes from whole-genome sequence (WGS) samples simultaneously. The MuDoGeR v1.0 framework acts as a wrapper for several tools. It was designed to be an easy-to-use tool that outputs ready-to-use comprehensive files.", "homepage": "https://github.com/mdsufz/MuDoGeR", "biotoolsID": "mudoger", "biotoolsCURIE": "biotools:mudoger", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0310", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3673", "term": "Whole genome sequencing" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" }, { "uri": "http://edamontology.org/topic_0084", "term": "Phylogeny" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Shell", "R", "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/mdsufz/MuDoGeR", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1111/1755-0998.13904", "pmid": "37994269", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "MuDoGeR: Multi-Domain Genome recovery from metagenomes made easy", "abstract": "Several computational frameworks and workflows that recover genomes from prokaryotes, eukaryotes and viruses from metagenomes exist. Yet, it is difficult for scientists with little bioinformatics experience to evaluate quality, annotate genes, dereplicate, assign taxonomy and calculate relative abundance and coverage of genomes belonging to different domains. MuDoGeR is a user-friendly tool tailored for those familiar with Unix command-line environment that makes it easy to recover genomes of prokaryotes, eukaryotes and viruses from metagenomes, either alone or in combination. We tested MuDoGeR using 24 individual-isolated genomes and 574 metagenomes, demonstrating the applicability for a few samples and high throughput. While MuDoGeR can recover eukaryotic viral sequences, its characterization is predominantly skewed towards bacterial and archaeal viruses, reflecting the field's current state. However, acting as a dynamic wrapper, the MuDoGeR is designed to constantly incorporate updates and integrate new tools, ensuring its ongoing relevance in the rapidly evolving field. MuDoGeR is open-source software available at https://github.com/mdsufz/MuDoGeR. Additionally, MuDoGeR is also available as a Singularity container.", "date": "2024-02-01T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Rocha U." }, { "name": "CoelhoKasmanas J." }, { "name": "Kallies R." }, { "name": "Saraiva J.P." }, { "name": "Toscan R.B." }, { "name": "Stefanic P." }, { "name": "Bicalho M.F." }, { "name": "BorimCorrea F." }, { "name": "Basturk M.N." }, { "name": "Fousekis E." }, { "name": "VianaBarbosa L.M." }, { "name": "Plewka J." }, { "name": "Probst A.J." }, { "name": "Baldrian P." }, { "name": "Stadler P.F." } ], "journal": "Molecular Ecology Resources" } } ], "credit": [ { "name": "Ulisses Rocha", "email": "ulisses.rocha@ufz.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "Pub2Tools", "additionDate": "2024-04-16T14:14:05.166974Z", "lastUpdate": "2025-04-09T07:23:51.614291Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "CheckM2", "description": "Rapid assessment of genome bin quality using machine learning.\n\nCheckM2 uses two distinct machine learning models to predict genome completeness. The 'general' gradient boost model is able to generalize well and is intended to be used on organisms not well represented in GenBank or RefSeq (roughly, when an organism is novel at the level of order, class or phylum). The 'specific' neural network model is more accurate when predicting completeness of organisms more closely related to the reference training set (roughly, when an organism belongs to a known species, genus or family). CheckM2 uses a cosine similarity calculation to automatically determine the appropriate completeness model for each input genome, but you can also force the use of a particular completeness model, or get the prediction outputs for both. There is only one contamination model (based on gradient boost) which is applied regardless of taxonomic novelty and works well across all cases.", "homepage": "https://github.com/chklovski/CheckM2", "biotoolsID": "checkm2", "biotoolsCURIE": "biotools:checkm2", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_0194", "term": "Phylogenomics" }, { "uri": "http://edamontology.org/topic_3572", "term": "Data quality management" } ], "operatingSystem": [ "Linux" ], "language": [], "license": "GPL-3.0", "collectionID": [ "NFDI4Microbiota" ], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.nature.com/articles/s41592-023-01940-w", "type": [ "Other" ], "note": null } ], "download": [ { "url": "https://doi.org/10.5281/zenodo.14897628", "type": "Biological data", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/chklovski/CheckM2", "type": [ "Quick start guide" ], "note": null } ], "publication": [ { "doi": "10.1038/s41592-023-01940-w", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "Kasmanas", "additionDate": "2025-04-08T11:23:25.060891Z", "lastUpdate": "2025-04-08T11:23:25.063938Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PSIPRED", "description": "The PSIPRED Protein Analysis Workbench unites many available analysis tools into a single web based framework. An excellent tool for prediction of secondary structure, with access to GenTHREADER for protein fold recognition and MEMSAT-2 transmembrane topology prediction.", "homepage": "http://bioinf.cs.ucl.ac.uk/psipred/", "biotoolsID": "psipred", "biotoolsCURIE": "biotools:psipred", "version": [], "otherID": [ { "value": "RRID:SCR_018546", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0469", "term": "Protein secondary structure prediction (turns)" }, { "uri": "http://edamontology.org/operation_0303", "term": "Protein fold recognition" }, { "uri": "http://edamontology.org/operation_0267", "term": "Protein secondary structure prediction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0082", "term": "Structure prediction" }, { "uri": "http://edamontology.org/topic_0736", "term": "Protein folds and structural domains" }, { "uri": "http://edamontology.org/topic_3542", "term": "Protein secondary structure" }, { "uri": "http://edamontology.org/topic_0130", "term": "Protein folding, stability and design" }, { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://bioinf.cs.ucl.ac.uk/index.php?id=779", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/16.4.404", "pmid": "10869041", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "The PSIPRED protein structure prediction server", "abstract": "The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method. Availability: Freely available to non-commercial users at http://globin.bio.warwick.ac.uk/psipred/.", "date": "2000-01-01T00:00:00Z", "citationCount": 3053, "authors": [ { "name": "McGuffin L.J." }, { "name": "Bryson K." }, { "name": "Jones D.T." } ], "journal": "Bioinformatics" } }, { "doi": "10.1006/jmbi.1999.3091", "pmid": "10493868", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Protein secondary structure prediction based on position-specific scoring matrices", "abstract": "A two-stage neural network has been used to predict protein secondary structure based on the position specific scoring matrices generated by PSI-BLAST. Despite the simplicity and convenience of the approach used, the results are found to be superior to those produced by other methods, including the popular PHD method according to our own benchmarking results and the results from the recent Critical Assessment of Techniques for Protein Structure Prediction experiment (CASP3), where the method was evaluated by stringent blind testing. Using a new testing set based on a set of 187 unique folds, and three-way cross-validation based on structural similarity criteria rather than sequence similarity criteria used previously (no similar folds were present in both the testing and training sets) the method presented here (PSIPRED) achieved an average Q3 score of between 76.5% to 78.3% depending on the precise definition of observed secondary structure used, which is the highest published score for any method to date. Given the success of the method in CASP3, it is reasonable to be confident that the evaluation presented here gives a fair indication of the performance of the method in general.", "date": "1999-09-17T00:00:00Z", "citationCount": 4685, "authors": [ { "name": "Jones D.T." } ], "journal": "Journal of Molecular Biology" } }, { "doi": "10.1093/nar/gkt381", "pmid": "23748958", "pmcid": "PMC3692098", "type": [], "version": null, "note": null, "metadata": { "title": "Scalable web services for the PSIPRED Protein Analysis Workbench.", "abstract": "Here, we present the new UCL Bioinformatics Group's PSIPRED Protein Analysis Workbench. The Workbench unites all of our previously available analysis methods into a single web-based framework. The new web portal provides a greatly streamlined user interface with a number of new features to allow users to better explore their results. We offer a number of additional services to enable computationally scalable execution of our prediction methods; these include SOAP and XML-RPC web server access and new HADOOP packages. All software and services are available via the UCL Bioinformatics Group website at http://bioinf.cs.ucl.ac.uk/.", "date": "2013-01-01T00:00:00Z", "citationCount": 1109, "authors": [ { "name": "Buchan D.W." }, { "name": "Minneci F." }, { "name": "Nugent T.C." }, { "name": "Bryson K." }, { "name": "Jones D.T." } ], "journal": "Nucleic acids research" } } ], "credit": [ { "name": "psipred team", "email": "psipred@cs.ucl.ac.uk", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Bijay", "additionDate": "2017-03-25T16:29:49Z", "lastUpdate": "2025-04-03T08:22:35.616168Z", "editPermission": { "type": "group", "authors": [ "zhouwj", "Bijay", "Yunus" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "neXtProt", "description": "neXtProt was an innovative knowledge platform dedicated to human proteins. This resource contained a wealth of high-quality data on all the human proteins that are produced by the 20'000 protein-coding genes found in the human genome. The content of neXtProt was continuously extended so as to provide many more carefully selected data sets and analysis tools. neXtProt data and tools have been archived.", "homepage": "https://www.expasy.org/archives/nextprot", "biotoolsID": "nextprot", "biotoolsCURIE": "biotools:nextprot", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2479", "term": "Protein sequence analysis" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" }, { "uri": "http://edamontology.org/operation_2406", "term": "Protein structure analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_0601", "term": "Protein modifications" }, { "uri": "http://edamontology.org/topic_3120", "term": "Protein variants" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "CC-BY-4.0", "collectionID": [ "Rare Disease", "Proteomics" ], "maturity": "Legacy", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [ "Data" ], "elixirNode": [ "Switzerland" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/calipho-sib/", "type": [ "Repository" ], "note": "neXtProt software repository with issue tracking" }, { "url": "https://twitter.com/nextprot_news", "type": [ "Social media" ], "note": "neXtProt release news, publications, presentations, tips and more. DM us with feedback!" }, { "url": "https://www.expasy.org/resources/nextprot", "type": [ "Software catalogue" ], "note": "neXtProt entry in Expasy" } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkz995", "pmid": "31724716", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The neXtProt knowledgebase in 2020: Data, tools and usability improvements", "abstract": "The neXtProt knowledgebase (https://www.nextprot.org) is an integrative resource providing both data on human protein and the tools to explore these. In order to provide comprehensive and up-to-date data, we evaluate and add new data sets. We describe the incorporation of three new data sets that provide expression, function, protein-protein binary interaction, post-translational modifications (PTM) and variant information. New SPARQL query examples illustrating uses of the new data were added. neXtProt has continued to develop tools for proteomics. We have improved the peptide uniqueness checker and have implemented a new protein digestion tool. Together, these tools make it possible to determine which proteases can be used to identify trypsin-resistant proteins by mass spectrometry. In terms of usability, we have finished revamping our web interface and completely rewritten our API. Our SPARQL endpoint now supports federated queries. All the neXtProt data are available via our user interface, API, SPARQL endpoint and FTP site, including the new PEFF 1.0 format files. Finally, the data on our FTP site is now CC BY 4.0 to promote its reuse.", "date": "2020-01-01T00:00:00Z", "citationCount": 155, "authors": [ { "name": "Zahn-Zabal M." }, { "name": "Michel P.-A." }, { "name": "Gateau A." }, { "name": "Nikitin F." }, { "name": "Schaeffer M." }, { "name": "Audot E." }, { "name": "Gaudet P." }, { "name": "Duek P.D." }, { "name": "Teixeira D." }, { "name": "De Laval V.R." }, { "name": "Samarasinghe K." }, { "name": "Bairoch A." }, { "name": "Lane L." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkr1179", "pmid": "22139911", "pmcid": "PMC3245017", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "NeXtProt: A knowledge platform for human proteins", "abstract": "neXtProt (http://www.nextprot.org/) is a new human protein-centric knowledge platform. Developed at the Swiss Institute of Bioinformatics (SIB), it aims to help researchers answer questions relevant to human proteins. To achieve this goal, neXtProt is built on a corpus containing both curated knowledge originating from the UniProtKB/Swiss-Prot knowledgebase and carefully selected and filtered high-throughput data pertinent to human proteins. This article presents an overview of the database and the data integration process. We also lay out the key future directions of neXtProt that we consider the necessary steps to make neXtProt the one-stop-shop for all research projects focusing on human proteins. © The Author(s) 2011.", "date": "2012-01-01T00:00:00Z", "citationCount": 168, "authors": [ { "name": "Lane L." }, { "name": "Argoud-Puy G." }, { "name": "Britan A." }, { "name": "Cusin I." }, { "name": "Duek P.D." }, { "name": "Evalet O." }, { "name": "Gateau A." }, { "name": "Gaudet P." }, { "name": "Gleizes A." }, { "name": "Masselot A." }, { "name": "Zwahlen C." }, { "name": "Bairoch A." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "SIB Swiss Institute of Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Support", "email": "support@nextprot.org", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Pascale Gaudet", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0003-1813-6857", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "SIB", "additionDate": "2015-01-21T13:30:06Z", "lastUpdate": "2025-04-02T08:05:19.163091Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "mzahn", "LanfearJ" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "csdR", "description": "Differential gene coexpression analysis based on the Conserved, Specific, and Differentiated (CSD) method", "homepage": "https://almaaslab.github.io/csdR/", "biotoolsID": "csdr", "biotoolsCURIE": "biotools:csdr", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" }, { "uri": "http://edamontology.org/topic_0085", "term": "Functional genomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.bioconductor.org/packages/release/bioc/html/csdR.html", "type": [ "Software catalogue" ], "note": null }, { "url": "https://github.com/AlmaasLab/csdR", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/s12859-022-04605-1", "pmid": "35183100", "pmcid": "PMC8858518", "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "csdR, an R package for differential co-expression analysis", "abstract": "Background: Differential co-expression network analysis has become an important tool to gain understanding of biological phenotypes and diseases. The CSD algorithm is a method to generate differential co-expression networks by comparing gene co-expressions from two different conditions. Each of the gene pairs is assigned conserved (C), specific (S) and differentiated (D) scores based on the co-expression of the gene pair between the two conditions. The result of the procedure is a network where the nodes are genes and the links are the gene pairs with the highest C-, S-, and D-scores. However, the existing CSD-implementations suffer from poor computational performance, difficult user procedures and lack of documentation. Results: We created the R-package csdR aimed at reaching good performance together with ease of use, sufficient documentation, and with the ability to play well with other tools for data analysis. csdR was benchmarked on a realistic dataset with 20,645 genes. After verifying that the chosen number of iterations gave sufficient robustness, we tested the performance against the two existing CSD implementations. csdR was superior in performance to one of the implementations, whereas the other did not run. Our implementation can utilize multiple processing cores. However, we were unable to achieve more than ∼ 2.7 parallel speedup with saturation reached at about 10 cores. Conclusion: The results suggest that csdR is a useful tool for differential co-expression analysis and is able to generate robust results within a workday on datasets of realistic sizes when run on a workstation or compute server.", "date": "2022-12-01T00:00:00Z", "citationCount": 3, "authors": [ { "name": "Pettersen J.P." }, { "name": "Almaas E." } ], "journal": "BMC Bioinformatics" } } ], "credit": [], "owner": "japet", "additionDate": "2025-03-31T08:50:20.800385Z", "lastUpdate": "2025-03-31T09:00:57.202555Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "WeSA", "description": "WeSA, (weighted socioaffinity), is a statistical score which can rank results from protein experiments of the bait-prey type, e.g. affinity purification, immunoprecipitation or proximity labelling.\n\nYou can enter lists of interacting proteins according to the results of your experiment. Input your raw data before any filtering is done.\n\nAs a result you will get a re-ordered list of scores which allows one to understand which interactions are more likely than others based on what previous experiments can add to your data.", "homepage": "https://wesa.russelllab.org/", "biotoolsID": "we_sa", "biotoolsCURIE": "biotools:we_sa", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3957", "term": "Protein interaction experiment" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/russelllab/wesa", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://wesa.russelllab.org/help", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkae423", "pmid": "38795065", "pmcid": "PMC11223876", "type": [], "version": null, "note": null, "metadata": { "title": "WeSA: A web server for improving analysis of affinity proteomics data", "abstract": "Protein-protein interaction experiments still yield many false positive interactions. The socioaffinity metric can distinguish true protein-protein interactions from noise based on available data. Here, we present WeSA (Weighted SocioAffinity), which considers large datasets of interaction proteomics data (IntAct, BioGRID, the BioPlex) to score human protein interactions and, in a statistically robust way, flag those (even from a single experiment) that are likely to be false positives. ROC analysis (using CORUM-PDB positives and Negatome negatives) shows that WeSA improves over other measures of interaction confidence. WeSA shows consistently good results over all datasets (up to: AUC = 0.93 and at best threshold: TPR = 0.84, FPR = 0.11, Precision = 0.98). WeSA is freely available without login (wesa.russelllab.org). Users can submit their own data or look for organized information on human protein interactions using the web server. Users can either retrieve available information for a list of proteins of interest or calculate scores for new experiments. The server outputs either pre-computed or updated WeSA scores for the input enriched with information from databases. The summary is presented as a table and a network-based visualization allowing the user to remove those nodes/edges that the method considers spurious.", "date": "2024-07-05T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Shtetinska M.M." }, { "name": "Gonzalez-Sanchez J.-C." }, { "name": "Beyer T." }, { "name": "Boldt K." }, { "name": "Ueffing M." }, { "name": "Russell R.B." } ], "journal": "Nucleic Acids Research" } } ], "credit": [], "owner": "Pub2Tools", "additionDate": "2025-03-28T11:13:12.813456Z", "lastUpdate": "2025-03-28T12:14:32.901305Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "ChemFH", "description": "An integrated online platform developed for the screening and prediction of potential frequent drug hitters, thus improving the efficiency of drug R&D in colloidal aggregate, firefly luciferase reporter enzyme inhibition, fluorescence, chemical reactivity, and promiscuity. ChemFH: an integrated tool for screening frequent false positives in chemical biology and drug discovery.", "homepage": "https://chemfh.scbdd.com/", "biotoolsID": "chemfh", "biotoolsCURIE": "biotools:chemfh", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3938", "term": "Virtual screening" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2301", "term": "SMILES string" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1696", "term": "Drug report" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1712", "term": "Chemical structure image" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Script", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0209", "term": "Medicinal chemistry" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "JavaScript" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/antwiser/ChemFH", "type": [ "Repository" ], "note": null }, { "url": "https://chemfh.scbdd.com/", "type": [ "Other" ], "note": "Webpage of the tool" } ], "download": [ { "url": "https://github.com/antwiser/ChemFH/releases/tag/ChemFH-1.0.0", "type": "Source code", "note": null, "version": "1.0.0" } ], "documentation": [ { "url": "https://github.com/antwiser/ChemFH/blob/main/README.md", "type": [ "General" ], "note": null }, { "url": "https://chemfh.scbdd.com/documentation/#/", "type": [ "Quick start guide" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkae424", "pmid": "38783035", "pmcid": "PMC11223804", "type": [ "Method" ], "version": "1.0.0", "note": "High-throughput screening rapidly tests an extensive array of chemical compounds to identify hit compounds for specific biological targets in drug discovery. However, false-positive results disrupt hit compound screening, leading to wastage of time and resources. To address this, we propose ChemFH, an integrated online platform facilitating rapid virtual evaluation of potential false positives, including colloidal aggregators, spectroscopic interference compounds, firefly luciferase inhibitors, chemical reactive compounds, promiscuous compounds, and other assay interferences. ChemFH is freely available via https://chemfh.scbdd.com/.", "metadata": { "title": "ChemFH: An integrated tool for screening frequent false positives in chemical biology and drug discovery", "abstract": "High-throughput screening rapidly tests an extensive array of chemical compounds to identify hit compounds for specific biological targets in drug discovery. However, false-positive results disrupt hit compound screening, leading to wastage of time and resources. To address this, we propose ChemFH, an integrated online platform facilitating rapid virtual evaluation of potential false positives, including colloidal aggregators, spectroscopic interference compounds, firefly luciferase inhibitors, chemical reactive compounds, promiscuous compounds, and other assay interferences. By leveraging a dataset containing 823 391 compounds, we constructed high-quality prediction models using multi-task directed message-passing network (DMPNN) architectures combining uncertainty estimation, yielding an average AUC value of 0.91. Furthermore, ChemFH incorporated 1441 representative alert substructures derived from the collected data and ten commonly used frequent hitter screening rules. ChemFH was validated with an external set of 75 compounds. Subsequently, the virtual screening capability of ChemFH was successfully confirmed through its application to five virtual screening libraries. Furthermore, ChemFH underwent additional validation on two natural products and FDA-approved drugs, yielding reliable and accurate results. ChemFH is a comprehensive, reliable, and computationally efficient screening pipeline that facilitates the identification of true positive results in assays, contributing to enhanced efficiency and success rates in drug discovery. ChemFH is freely available via https://chemfh.scbdd.com/.", "date": "2024-07-05T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Shi S." }, { "name": "Fu L." }, { "name": "Yi J." }, { "name": "Yang Z." }, { "name": "Zhang X." }, { "name": "Deng Y." }, { "name": "Wang W." }, { "name": "Wu C." }, { "name": "Zhao W." }, { "name": "Hou T." }, { "name": "Zeng X." }, { "name": "Lyu A." }, { "name": "Cao D." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Jiacai Yi", "email": "yjc@nudt.edu.cn", "url": "https://github.com/antwiser", "orcidid": "https://orcid.org/0000-0001-6823-1882", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "National University of Defense Technology, Changsha, Hunan" } ], "owner": "etepf22", "additionDate": "2025-03-28T11:01:52.929561Z", "lastUpdate": "2025-03-28T12:04:07.529430Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "LncRNAway", "description": "A web-based sgRNA design tool for precise and effective suppression of long noncoding RNAs", "homepage": "https://www.lncrnaway.com", "biotoolsID": "lncrnaway", "biotoolsCURIE": "biotools:lncrnaway", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0230", "term": "Sequence generation" }, { "uri": "http://edamontology.org/operation_0308", "term": "PCR primer design" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1033", "term": "Ensembl gene ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1026", "term": "Gene symbol" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3495", "term": "RNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_2305", "term": "GFF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3495", "term": "RNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_0972", "term": "Text mining report" }, "format": [] } ], "note": "Design of sgRNA for lncRNA knockout; Primer design for PCR and qPCR to knockout detection.", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0085", "term": "Functional genomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.lncrnaway.com", "type": [ "Service" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkae383", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "LncRNAway: A web-based sgRNA design tool for precise and effective suppression of long noncoding RNAs", "abstract": "Thousands of long noncoding RNAs (lncRNAs) have been annotated via high-throughput RNA sequencing, yet only a small fraction have been functionally investigated. Genomic knockout is the mainstream strategy for studying the biological function of protein-coding genes and lncRNAs, whereas the complexity of the lncRNA locus, especially the natural antisense lncRNAs (NAT-lncRNAs), presents great challenges. Knocking out lncRNAs often results in unintended disruptions of neighboring protein-coding genes and small RNAs, leading to ambiguity in observing phenotypes and interpreting biological function. To address this issue, we launched LncRNAway, a user-friendly web tool based on the BESST (branchpoint to 3' splicing site targeting) method, to design sgRNAs for lncRNA knockout. LncRNAway not only provides specific and effective lncRNA knockout guidelines but also integrates genotyping primers and quantitative PCR primers designing, thereby streamlining experimental procedures of lncRNA function study. LncRNAway is freely available at https://www.lncrnaway.com.", "date": "2024-07-05T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Zhang S." }, { "name": "Wang S." }, { "name": "Lu F." }, { "name": "Bie L." }, { "name": "Luo Y." }, { "name": "Sun J." }, { "name": "Zhang Y." }, { "name": "Wang Y." }, { "name": "Zhang Y." }, { "name": "Lyu Q.R." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Chongqing General Hospital, Chongqing University, Lyu Lab", "email": "qlyu@cqu.edu.cn", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "inespinheiro", "additionDate": "2025-03-28T11:01:27.681477Z", "lastUpdate": "2025-03-28T11:54:36.402981Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "IsoVis", "description": "A webserver for visualization and annotation of alternative RNA isoforms", "homepage": "https://isomix.org/isovis/", "biotoolsID": "isovis", "biotoolsCURIE": "biotools:isovis", "version": [ "v1.10" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2877", "term": "Protein complex" }, "format": [ { "uri": "http://edamontology.org/format_2305", "term": "GFF" }, { "uri": "http://edamontology.org/format_2306", "term": "GTF" }, { "uri": "http://edamontology.org/format_3003", "term": "BED" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0883", "term": "Structure" }, "format": [] } ], "note": "isoform stack", "cmd": "--" } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_4019", "term": "Biosciences" } ], "operatingSystem": [ "Linux", "Windows" ], "language": [ "JavaScript" ], "license": "MPL-2.0", "collectionID": [ "IsoVis" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "UK" ], "elixirCommunity": [], "link": [ { "url": "https://isomix.org/isovis/", "type": [ "Other" ], "note": "a webserver" }, { "url": "https://github.com/ClarkLaboratory/IsoVis?tab=MPL-2.0-1-ov-file", "type": [ "Repository" ], "note": null }, { "url": "https://academic.oup.com/nar/article/52/W1/W341/7665639", "type": [ "Other" ], "note": "Nucleic Acids Research" } ], "download": [ { "url": "https://github.com/ClarkLaboratory/IsoVis.git", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://isovis.gandallab.org/tutorial/", "type": [ "User manual" ], "note": null } ], "publication": [], "credit": [], "owner": "Kvetoslava_Mahutova", "additionDate": "2025-03-28T11:20:32.972026Z", "lastUpdate": "2025-03-28T11:41:10.718643Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DDMut-PPI", "description": "A deep learning model that efficiently and accurately predicts the changes in PPI binding free energy upon single and multiple point mutations.", "homepage": "https://biosig.lab.uq.edu.au/ddmut_ppi/", "biotoolsID": "ddmut-ppi", "biotoolsCURIE": "biotools:ddmut-ppi", "version": [], "otherID": [], "relation": [ { "biotoolsID": "tensorflow", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0276", "term": "Protein interaction network analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2526", "term": "Text data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [] } ], "note": "Single Prediction - Job Submission", "cmd": "$ curl https://biosig.lab.uq.edu.au/ddmut_ppi/api/single -X POST -i -F pdb_file=@/home/ubuntu/1cse.pdb -F mutation=L45G -F chain=I -F reverse=True" } ], "toolType": [ "Web API" ], "topic": [ { "uri": "http://edamontology.org/topic_3332", "term": "Computational chemistry" } ], "operatingSystem": [ "Linux" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://biosig.lab.uq.edu.au/ddmut_ppi/datasets", "type": "Biological data", "note": null, "version": null } ], "documentation": [ { "url": "https://biosig.lab.uq.edu.au/ddmut_ppi/api", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkae412", "pmid": "38783112", "pmcid": "PMC11223791", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "DDMut-PPI: Predicting effects of mutations on protein-protein interactions using graph-based deep learning", "abstract": "Protein-protein interactions (PPIs) play a vital role in cellular functions and are essential for therapeutic development and understanding diseases. However, current predictive tools often struggle to balance efficiency and precision in predicting the effects of mutations on these complex interactions. To address this, we present DDMut-PPI, a deep learning model that efficiently and accurately predicts changes in PPI binding free energy upon single and multiple point mutations. Building on the robust Siamese network architecture with graph-based signatures from our prior work, DDMut, the DDMut-PPI model was enhanced with a graph convolutional network operated on the protein interaction interface. We used residue-specific embeddings from ProtT5 protein language model as node features, and a variety of molecular interactions as edge features. By integrating evolutionary context with spatial information, this framework enables DDMut-PPI to achieve a robust Pearson correlation of up to 0.75 (root mean squared error: 1.33 kcal/mol) in our evaluations, outperforming most existing methods. Importantly, the model demonstrated consistent performance across mutations that increase or decrease binding affinity. DDMut-PPI offers a significant advancement in the field and will serve as a valuable tool for researchers probing the complexities of protein interactions. DDMut-PPI is freely available as a web server and an application programming interface at https://biosig.lab.uq.edu.au/ddmut_ppi.", "date": "2024-07-05T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Zhou Y." }, { "name": "Myung Y." }, { "name": "Rodrigues C.H.M." }, { "name": "Ascher D.B." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": null, "email": null, "url": "https://biosig.lab.uq.edu.au/contact", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "TomasGeraldes", "additionDate": "2025-03-28T11:04:18.911217Z", "lastUpdate": "2025-03-28T11:05:03.279672Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "prolfquapp", "description": "A command-line tool for differential expression analysis in quantitative proteomics", "homepage": "https://github.com/prolfqua/prolfquapp", "biotoolsID": "prolfquapp", "biotoolsCURIE": "biotools:prolfquapp", "version": [ "0.1.6" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3741", "term": "Differential protein expression profiling" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3620", "term": "xlsx" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": "./prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y config.yaml -w NameOfAnalysis -s DIANN\n# and again you run the version within the docker container with\n# ./prolfquapp_docker.sh prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y config.yaml -w NameOfAnalysis -s DIANN" }, { "operation": [ { "uri": "http://edamontology.org/operation_2428", "term": "Validation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3620", "term": "xlsx" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3914", "term": "Quality control report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0571", "term": "Expression data visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "R" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/prolfqua/prolfquapp", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/prolfqua/prolfquapp/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/prolfqua/prolfquapp/releases/tag/0.1.6", "type": "Downloads page", "note": null, "version": "0.1.6" } ], "documentation": [ { "url": "https://github.com/prolfqua/prolfquapp/blob/master/README.md", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jproteome.4c00911", "pmid": null, "pmcid": null, "type": [], "version": "0.0.6", "note": null, "metadata": { "title": "prolfquapp ─ A User-Friendly Command-Line Tool Simplifying Differential Expression Analysis in Quantitative Proteomics", "abstract": "Mass spectrometry is a cornerstone of quantitative proteomics, enabling relative protein quantification and differential expression analysis (DEA) of proteins. As experiments grow in complexity, involving more samples, groups, and identified proteins, interactive differential expression analysis tools become impractical. The prolfquapp addresses this challenge by providing a command-line interface that simplifies DEA, making it accessible to nonprogrammers and seamlessly integrating it into workflow management systems. Prolfquapp streamlines data processing and result visualization by generating dynamic HTML reports that facilitate the exploration of differential expression results. These reports allow for investigating complex experiments, such as those involving repeated measurements or multiple explanatory variables. Additionally, prolfquapp supports various output formats, including XLSX files, SummarizedExperiment objects and rank files, for further interactive analysis using spreadsheet software, the exploreDE Shiny application, or gene set enrichment analysis software, respectively. By leveraging advanced statistical models from the prolfqua R package, prolfquapp offers a user-friendly, integrated solution for large-scale quantitative proteomics studies, combining efficient data processing with insightful, publication-ready outputs.", "date": "2025-02-07T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Wolski W.E." }, { "name": "Grossmann J." }, { "name": "Schwarz L." }, { "name": "Leary P." }, { "name": "Turker C." }, { "name": "Nanni P." }, { "name": "Schlapbach R." }, { "name": "Panse C." } ], "journal": "Journal of Proteome Research" } } ], "credit": [], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2025-02-28T15:04:33.594183Z", "lastUpdate": "2025-03-28T10:18:25.715685Z", "editPermission": { "type": "group", "authors": [ "thatmariia" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "WorkflowHub", "description": "WorkflowHub is a registry for describing, sharing and publishing scientific computational workflows.\n\nThe registry supports any workflow in its native repository.\n\nWorkflowHub aims to facilitate discovery and re-use of workflows in an accessible and interoperable way. 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Gene coexpression analysis allows the discovery of functional gene partners or the assignment of biological roles to genes of unknown function. In this protocol, we describe the steps necessary to create a gene coexpression tree for Arabidopsis thaliana, using publicly available Affymetrix CEL microarray data. Because the computational analysis described here is highly dependent on sample quality, we detail an automatic quality control approach. For complete details on the use and execution of this protocol, please refer to Zogopoulos et al. (2021).", "date": "2022-03-18T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Zogopoulos V.L." }, { "name": "Malatras A." }, { "name": "Michalopoulos I." } ], "journal": "STAR Protocols" } }, { "doi": "10.3390/biology11071019", "pmid": "36101400", "pmcid": "PMC9312353", "type": [ "Review" ], "version": null, "note": null, "metadata": { "title": "Approaches in Gene Coexpression Analysis in Eukaryotes", "abstract": "Gene coexpression analysis constitutes a widely used practice for gene partner identification and gene function prediction, consisting of many intricate procedures. The analysis begins with the collection of primary transcriptomic data and their preprocessing, continues with the calculation of the similarity between genes based on their expression values in the selected sample dataset and results in the construction and visualisation of a gene coexpression network (GCN) and its evaluation using biological term enrichment analysis. As gene coexpression analysis has been studied ex-tensively, we present most parts of the methodology in a clear manner and the reasoning behind the selection of some of the techniques. In this review, we offer a comprehensive and comprehensi-ble account of the steps required for performing a complete gene coexpression analysis in eukary-otic organisms. We comment on the use of RNA‐Seq vs. microarrays, as well as the best practices for GCN construction. 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A database stores pre-calculated co-expression results for ∼21 800 genes based on data from over 300 arrays. These results can be corroborated by calculation of co-expression results for user-defined sub-sets of arrays or experiments from the NASC/GARNet array dataset. Clique Finder (CF) identifies groups of genes which are consistently co-expressed with each other across a user-defined co-expression list. The parameters can be altered easily to adjust cluster size and the output examined for optimal inclusion of genes with known biological roles. Alternatively, a Scatter Plot tool displays the correlation coefficients for all genes against two user-selected queries on a scatter plot which can be useful for visual identification of clusters of genes with similar r-values. User-input groups of genes can be highlighted on the scatter plots. Inclusion of genes with known biology in sets of genes identified using CF and Scatter Plot tools allows inferences to be made about the roles of the other genes in the set and both tools can therefore be used to generate short lists of genes for further characterization. ACT is freely available at www.Arabidopsis.leeds.ac.uk/ACT. © The Author 2006. Published by Oxford University Press. All rights reserved.", "date": "2006-07-01T00:00:00Z", "citationCount": 130, "authors": [ { "name": "Manfield I.W." }, { "name": "Jen C.-H." }, { "name": "Pinney J.W." }, { "name": "Michalopoulos I." }, { "name": "Bradford J.R." }, { "name": "Gilmartin P.M." }, { "name": "Westhead D.R." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1111/j.1365-313x.2006.02681.x", "pmid": "16623895", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "The Arabidopsis co-expression tool (ACT): A WWW-based tool and database for microarray-based gene expression analysis", "abstract": "We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (ACT), based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression patterns are correlated across selected experiments or the complete data set. Results are accompanied by estimates of the statistical significance of the correlation relationships, expressed as probability (P) and expectation (E) values. Additionally, highly ranked genes on a correlation list can be examined using the novel CLIQUE FINDER tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots, and dissection into cliques of co-regulated genes. We illustrate the applications of the software by analysing genes encoding functionally related proteins, as well as pathways involved in plant responses to environmental stimuli. These analyses demonstrate novel biological relationships underlying the observed gene co-expression patterns. To demonstrate the ability of the software to develop testable hypotheses on gene function within a defined biological process we have used the example of cell wall biosynthesis genes. The resource is freely available at http://www.arabidopsis.leeds.ac.uk/ACT/. © 2006 The Authors.", "date": "2006-04-01T00:00:00Z", "citationCount": 65, "authors": [ { "name": "Jen C.-H." }, { "name": "Manfield I.W." }, { "name": "Michalopoulos I." }, { "name": "Pinney J.W." }, { "name": "Willats W.G.T." }, { "name": "Gilmartin P.M." }, { "name": "Westhead D.R." } ], "journal": "Plant Journal" } }, { "doi": "10.1016/j.isci.2021.102848", "pmid": "34381973", "pmcid": "PMC8334378", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Arabidopsis Coexpression Tool: a tool for gene coexpression analysis in Arabidopsis thaliana", "abstract": "Gene coexpression analysis refers to the discovery of sets of genes which exhibit similar expression patterns across multiple transcriptomic data sets, such as microarray experiment data of public repositories. Arabidopsis Coexpression Tool (ACT), a gene coexpression analysis web tool for Arabidopsis thaliana, identifies genes which are correlated to a driver gene. Primary microarray data from ATH1 Affymetrix platform were processed with Single-Channel Array Normalization algorithm and combined to produce a coexpression tree which contains ∼21,000 A. thaliana genes. ACT was developed to present subclades of coexpressed genes, as well as to perform gene set enrichment analysis, being unique in revealing enriched transcription factors targeting coexpressed genes. ACT offers a simple and user-friendly interface producing working hypotheses which can be experimentally verified for the discovery of gene partnership, pathway membership, and transcriptional regulation. ACT analyses have been successful in identifying not only genes with coordinated ubiquitous expressions but also genes with tissue-specific expressions.", "date": "2021-08-20T00:00:00Z", "citationCount": 14, "authors": [ { "name": "Zogopoulos V.L." }, { "name": "Saxami G." }, { "name": "Malatras A." }, { "name": "Angelopoulou A." }, { "name": "Jen C.-H." }, { "name": "Duddy W.J." }, { "name": "Daras G." }, { "name": "Hatzopoulos P." }, { "name": "Westhead D.R." }, { "name": "Michalopoulos I." } ], "journal": "iScience" } } ], "credit": [ { "name": "David R Westhead", "email": "D.R.Westhead@leeds.ac.uk", "url": "https://biologicalsciences.leeds.ac.uk/molecular-and-cellular-biology/staff/154/professor-david-r-westhead", "orcidid": "https://orcid.org/0000-0002-0519-3820", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Ioannis Michalopoulos", "email": "imichalop@bioacademy.gr", "url": "https://www.michalopoulos.net/", "orcidid": "https://orcid.org/0000-0001-8991-8712", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "imichalop@bioacademy.gr", "additionDate": "2017-02-10T14:14:47Z", "lastUpdate": "2025-03-10T11:30:02.403040Z", "editPermission": { "type": "private", "authors": [ "imichalop@bioacademy.gr" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "vcztools", "description": "Partial reimplementation of bcftools for VCF Zarr.", "homepage": "https://sgkit-dev.github.io/vcztools", "biotoolsID": "vcztools", "biotoolsCURIE": "biotools:vcztools", "version": [], "otherID": [], "relation": [ { "biotoolsID": "bcftools", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3434", "term": "Conversion" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [], "operatingSystem": [ "Mac", "Linux" ], "language": [ "Python" ], "license": null, "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://pypi.org/project/vcztools/", "type": "Software package", "note": null, "version": null } ], "documentation": [ { "url": "https://sgkit-dev.github.io/vcztools", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1101/2024.06.11.598241", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "jeromekelleher", "additionDate": "2025-03-05T12:29:30.574691Z", "lastUpdate": "2025-03-05T12:29:30.686051Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "bio2zarr", "description": "Converts bioinformatics formats to Zarr.", "homepage": "https://sgkit-dev.github.io/bio2zarr/", "biotoolsID": "bio2zarr", "biotoolsCURIE": "biotools:bio2zarr", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3434", "term": "Conversion" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3071", "term": "Data management" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "Python" ], "license": null, "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://pypi.org/project/bio2zarr/", "type": "Software package", "note": null, "version": null } ], "documentation": [ { "url": "https://sgkit-dev.github.io/bio2zarr/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1101/2024.06.11.598241", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "jeromekelleher", "additionDate": "2025-03-05T12:15:13.884547Z", "lastUpdate": "2025-03-05T12:15:13.898661Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "AutoBIGS.CLI", "description": "A command-line interface (CLI) based program that allows quickly batched requests for obtaining MLST profiles on multiple FASTA sequences and exporting it as a convenient CSV. 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