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{ "count": 8851, "next": "?page=2", "previous": null, "list": [ { "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": "Galaxy Ecology", "description": "Galaxy Ecology is mainly developed by the French Data Terra research infrastructure Biodiversity data hub (PNDB). Its dedication is to provide tools for biodiversity data management and analysis for the Galaxy platform. Tools are useable through dedicated Galaxy instances hosted by Galaxy Europe (ecology.usegalaxy.eu) and Galaxy France (ecology.usegalaxy.fr).", "homepage": "https://github.com/galaxyecology/tools-ecology", "biotoolsID": "galaxy_ecology", "biotoolsCURIE": "biotools:galaxy_ecology", "version": [ "1.0.0" ], "otherID": [], "relation": [ { "biotoolsID": "galaxy", "type": "uses" }, { "biotoolsID": "tiaas", "type": "uses" }, { "biotoolsID": "Galaxy_Tools", "type": "uses" }, { "biotoolsID": "galaxy_france", "type": "includedIn" } ], "function": [], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3855", "term": "Environmental sciences" }, { "uri": "http://edamontology.org/topic_0610", "term": "Ecology" } ], "operatingSystem": [], "language": [], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://ecology.usegalaxy.eu", "type": [ "Galaxy service" ], "note": "European Galaxy Ecology instance" }, { "url": "https://ecology.usegalaxy.fr", "type": [ "Galaxy service" ], "note": "French Galaxy Ecology instance" } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/gigascience/giae122", "pmid": null, "pmcid": null, "type": [ "Review" ], "version": null, "note": null, "metadata": { "title": "Guidance framework to apply best practices in ecological data analysis: lessons learned from building Galaxy-Ecology", "abstract": "Numerous conceptual frameworks exist for best practices in research data and analysis (e.g., Open Science and FAIR principles). In practice, there is a need for further progress to improve transparency, reproducibility, and confidence in ecology. Here, we propose a practical and operational framework for researchers and experts in ecology to achieve best practices for building analytical procedures from individual research projects to production-level analytical pipelines. We introduce the concept of atomization to identify analytical steps that support generalization by allowing us to go beyond single analyses. The term atomization is employed to convey the idea of single analytical steps as \"atoms\"composing an analytical procedure. When generalized, \"atoms\"can be used in more than a single case analysis. These guidelines were established during the development of the Galaxy-Ecology initiative, a web platform dedicated to data analysis in ecology. Galaxy-Ecology allows us to demonstrate a way to reach higher levels of reproducibility in ecological sciences by increasing the accessibility and reusability of analytical workflows once atomized and generalized.", "date": "2025-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Royaux C." }, { "name": "Mihoub J.-B." }, { "name": "Josse M." }, { "name": "Pelletier D." }, { "name": "Norvez O." }, { "name": "Reecht Y." }, { "name": "Fouilloux A." }, { "name": "Rasche H." }, { "name": "Hiltemann S." }, { "name": "Batut B." }, { "name": "Marc E." }, { "name": "Seguineau P." }, { "name": "Masse G." }, { "name": "Amosse A." }, { "name": "Bissery C." }, { "name": "Lorrilliere R." }, { "name": "Martin A." }, { "name": "Bas Y." }, { "name": "Virgoulay T." }, { "name": "Chambon V." }, { "name": "Arnaud E." }, { "name": "Michon E." }, { "name": "Urfer C." }, { "name": "Trigodet E." }, { "name": "Delannoy M." }, { "name": "Lois G." }, { "name": "Julliard R." }, { "name": "Gruning B." }, { "name": "Le Bras Y." } ], "journal": "GigaScience" } } ], "credit": [ { "name": "Yvan Le Bras", "email": "yvan.le-bras@mnhn.fr", "url": null, "orcidid": "https://orcid.org/0000-0002-8504-068X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Muséum national d'Histoire naturelle", "email": null, "url": null, "orcidid": null, "gridid": "grid.410350.3", "rorid": "03wkt5x30", "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null } ], "owner": "ylebras", "additionDate": "2025-05-07T12:50:07.458170Z", "lastUpdate": "2025-05-07T12:50:07.461506Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "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": "EUCAIM Wizard Tool", "description": "The EUCAIM Wizard Tool performs an analysis of data re-identification risks of imaging and clinical data that follow the EUCAIM CDM. It includes and uses an EUCAIM specific configuration of the ARX Data Anonymization Tool (biotools:arx) for further anonymization, by supporting a wide variety of privacy and risk models as well methods for analyzing the usefulness of output data.", "homepage": "https://harbor.eucaim.cancerimage.eu/harbor/", "biotoolsID": "eucaim_wizard_tool", "biotoolsCURIE": "biotools:eucaim_wizard_tool", "version": [ "beta1.0" ], "otherID": [], "relation": [ { "biotoolsID": "arx", "type": "includes" }, { "biotoolsID": "arx", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3283", "term": "Anonymisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [ "EUCAIM" ], "maturity": null, "cost": null, "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/goharbor/harbor", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "vkalokyri", "additionDate": "2025-04-30T10:28:37.002350Z", "lastUpdate": "2025-05-01T12:43:46.544425Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "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. Rost", "email": "hannes.rost@utoronto.ca", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "samwein", "additionDate": "2019-08-09T13:16:33Z", "lastUpdate": "2025-04-30T11:39:29.549782Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "OpenSWATH", "description": "OpenSWATH is a proteomics software that allows analysis of LC-MS/MS DIA (data independent acquisition) and implemented as part of OpenMS.", "homepage": "http://www.openswath.org", "biotoolsID": "OpenSWATH", "biotoolsCURIE": "biotools:OpenSWATH", "version": [ "OpenMS 2.4.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0335", "term": "Formatting" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3108", "term": "Experimental measurement" }, "format": [ { "uri": "http://edamontology.org/format_3710", "term": "WIFF format" }, { "uri": "http://edamontology.org/format_3245", "term": "Mass spectrometry data format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3621", "term": "SQLite format" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3215", "term": "Peak detection" }, { "uri": "http://edamontology.org/operation_3628", "term": "Chromatographic alignment" }, { "uri": "http://edamontology.org/operation_3203", "term": "Chromatogram visualisation" }, { "uri": "http://edamontology.org/operation_3649", "term": "Target-Decoy" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass 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"uri": "http://edamontology.org/topic_3301", "term": "Microbiology" }, { "uri": "http://edamontology.org/topic_0821", "term": "Enzymes" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/database/bav033", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "BioSurfDB: Knowledge and algorithms to support biosurfactants and biodegradation studies", "abstract": "Crude oil extraction, transportation and use provoke the contamination of countless ecosystems. Therefore, bioremediation through surfactants mobilization or biodegradation is an important subject, both economically and environmentally. Bioremediation research had a great boost with the recent advances in Metagenomics, as it enabled the sequencing of uncultured microorganisms providing new insights on surfactant-producing and/or oil-degrading bacteria. Many research studies are making available genomic data from unknown organisms obtained from metagenomics analysis of oil-contaminated environmental samples. These new datasets are presently demanding the development of new tools and data repositories tailored for the biological analysis in a context of bioremediation data analysis. This work presents BioSurfDB, www.biosurfdb.org, a curated relational information system integrating data from: (i) metagenomes; (ii) organisms; (iii) biodegradation relevant genes; proteins and their metabolic pathways; (iv) bioremediation experiments results, with specific pollutants treatment efficiencies by surfactant producing organisms; and (v) a biosurfactant-curated list, grouped by producing organism, surfactant name, class and reference. The main goal of this repository is to gather information on the characterization of biological compounds and mechanisms involved in biosurfactant production and/or biodegradation and make it available in a curated way and associated with a number of computational tools to support studies of genomic and metagenomic data.", "date": "2015-01-01T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Oliveira J.S." }, { "name": "Araujo W." }, { "name": "Sales A.I.L." }, { "name": "De Brito Guerra A." }, { "name": "Da Silva Araujo S.C." }, { "name": "De Vasconcelos A.T.R." }, { "name": "Agnez-Lima L.F." }, { "name": "Freitas A.T." } ], "journal": "Database" } } ], "credit": [ { "name": "Jorge S. Oliveira", "email": "jorge.oliveira@tecnico.ulisboa.pt", "url": "https://web.tecnico.ulisboa.pt/jorge.oliveira/", "orcidid": "https://orcid.org/0000-0001-6425-2176", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Ana Teresa Freitas", "email": "ana.freitas@tecnico.ulisboa.pt", "url": null, "orcidid": "http://orcid.org/0000-0003-4638-2879", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Ana Tereza Ribeiro de Vasconcelos", "email": "atrv@lncc.br", "url": null, "orcidid": "http://orcid.org/0000-0002-4632-2086", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Lucymara Fassarella Agnez-Lima", "email": "lucymara.agnez@ufrn.br", "url": null, "orcidid": "http://orcid.org/0000-0003-0642-3162", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Gil Poiares-Oliveira", "email": "gpo@biodata.pt", "url": "https://web.tecnico.ulisboa.pt/gil.oliveira", "orcidid": "https://orcid.org/0000-0003-4638-2879", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null } ], "owner": "ELIXIR-PT", "additionDate": "2025-04-29T17:07:56.642694Z", "lastUpdate": "2025-04-29T17:35:41.655075Z", "editPermission": { "type": "group", "authors": [ "gpo" ] }, "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": "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": "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": "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": "The MINERVA Platform", "description": "The MINERVA (Molecular Interaction NEtwoRk VisuAlization) platform is a standalone webserver for visualization, exploration and management of molecular networks encoded in SBGN-compliant format, including files produced using CellDesigner or SBGN editors. Visualization of uploaded networks generated by the platform is accessible via a web browser to all viewers with the weblink to the resource.\n\nThe MINERVA Platform is a webservice using the Java Server Faces 2 technology. The server side, including data parsing, integration, annotation and verification, is implemented in Java. The platform uses the Postgres SQL database for data storage and the Hibernate framework as a middle layer between web server and database. The user web-interface is generated using React.js. The displayed content is visualized by OpenLayers API, dedicated JavaScript and CSS.", "homepage": "https://minerva.uni.lu", "biotoolsID": "MINERVA_Platform", "biotoolsCURIE": "biotools:MINERVA_Platform", "version": [ "13.1.3", "13.2.0", "14.0.13", "15.0.3", "16.4.0", "17.1.3", "18.1.1" ], "otherID": [], "relation": [ { "biotoolsID": "pathvisio", "type": "uses" }, { "biotoolsID": "sbgn", "type": "uses" }, { "biotoolsID": "libsbml", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3926", "term": "Pathway visualisation" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0571", "term": "Expression data visualisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_3391", "term": "Omics" }, { "uri": "http://edamontology.org/topic_3342", "term": "Translational medicine" } ], "operatingSystem": [], "language": [], "license": "AGPL-3.0", "collectionID": [ "ELIXIR-LU", "LCSB" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Luxembourg" ], "elixirCommunity": [], "link": [ { "url": "https://gitlab.lcsb.uni.lu/minerva/core/", "type": [ "Repository" ], "note": "GiLab repository for core functionalities (data and format handling, service stability, API access)" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/core/-/issues", "type": [ "Issue tracker" ], "note": "Issue tracker for core functionalities (data and format handling, service stability, API access)" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/frontend", "type": [ "Repository" ], "note": "GiLab repository for frontend functionalities" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/frontend/-/issues", "type": [ "Issue tracker" ], "note": "Issue tracker for frontend functionalities" } ], "download": [ { "url": "https://minerva.pages.uni.lu/doc/install/", "type": "Other", "note": "Installation instructions, including debian package, virtual machine images and docker containers.", "version": "13.1.3 - 18.1.1" } ], "documentation": [ { "url": "https://minerva.uni.lu", "type": [ "Quick start guide", "Release notes", "User manual", "API documentation", "Citation instructions", "Terms of use" ], "note": null } ], "publication": [ { "doi": "10.1038/npjsba.2016.20", "pmid": "28725475", "pmcid": "PMC5516855", "type": [ "Primary" ], "version": "10.0", "note": null, "metadata": { "title": "MINERVA—A platform for visualization and curation of molecular interaction networks", "abstract": "Our growing knowledge about various molecular mechanisms is becoming increasingly more structured and accessible. Different repositories of molecular interactions and available literature enable construction of focused and high-quality molecular interaction networks. Novel tools for curation and exploration of such networks are needed, in order to foster the development of a systems biology environment. In particular, solutions for visualization, annotation and data cross-linking will facilitate usage of network-encoded knowledge in biomedical research. To this end we developed the MINERVA (Molecular Interaction NEtwoRks VisuAlization) platform, a standalone webservice supporting curation, annotation and visualization of molecular interaction networks in Systems Biology Graphical Notation (SBGN)-compliant format. MINERVA provides automated content annotation and verification for improved quality control. The end users can explore and interact with hosted networks, and provide direct feedback to content curators. MINERVA enables mapping drug targets or overlaying experimental data on the visualized networks. Extensive export functions enable downloading areas of the visualized networks as SBGN-compliant models for efficient reuse of hosted networks. The software is available under Affero GPL 3.0 as a Virtual Machine snapshot, Debian package and Docker instance at http://r3lab.uni.lu/web/minerva-website/. We believe that MINERVA is an important contribution to systems biology community, as its architecture enables set-up of locally or globally accessible SBGN-oriented repositories of molecular interaction networks. Its functionalities allow overlay of multiple information layers, facilitating exploration of content and interpretation of data. Moreover, annotation and verification workflows of MINERVA improve the efficiency of curation of networks, allowing life-science researchers to better engage in development and use of biomedical knowledge repositories.", "date": "2016-01-01T00:00:00Z", "citationCount": 60, "authors": [ { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Satagopam V." }, { "name": "Gebel S." }, { "name": "Mazein A." }, { "name": "Kuzma M." }, { "name": "Zorzan S." }, { "name": "McGee F." }, { "name": "Otjacques B." }, { "name": "Balling R." }, { "name": "Schneider R." } ], "journal": "npj Systems Biology and Applications" } }, { "doi": "10.1093/bioinformatics/btz286", "pmid": "31074494", "pmcid": "PMC6821317", "type": [ "Primary" ], "version": "12.2.3", "note": null, "metadata": { "title": "MINERVA API and plugins: Opening molecular network analysis and visualization to the community", "abstract": "Summary: The complexity of molecular networks makes them difficult to navigate and interpret, creating a need for specialized software. MINERVA is a web platform for visualization, exploration and management of molecular networks. Here, we introduce an extension to MINERVA architecture that greatly facilitates the access and use of the stored molecular network data. It allows to incorporate such data in analytical pipelines via a programmatic access interface, and to extend the platform's visual exploration and analytics functionality via plugin architecture. This is possible for any molecular network hosted by the MINERVA platform encoded in well-recognized systems biology formats. To showcase the possibilities of the plugin architecture, we have developed several plugins extending the MINERVA core functionalities. In the article, we demonstrate the plugins for interactive tree traversal of molecular networks, for enrichment analysis and for mapping and visualization of known disease variants or known adverse drug reactions to molecules in the network. Availability and implementation: Plugins developed and maintained by the MINERVA team are available under the AGPL v3 license at https://git-r3lab.uni.lu/minerva/plugins/. The MINERVA API and plugin documentation is available at https://minerva-web.lcsb.uni.lu.", "date": "2019-11-01T00:00:00Z", "citationCount": 24, "authors": [ { "name": "Hoksza D." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Smula E." }, { "name": "Schneider R." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bib/bbz067", "pmid": "31273380", "pmcid": "PMC7373180", "type": [ "Primary" ], "version": "13.1.1", "note": null, "metadata": { "title": "Closing the gap between formats for storing layout information in systems biology", "abstract": "The understanding of complex biological networks often relies on both a dedicated layout and a topology. Currently, there are three major competing layout-aware systems biology formats, but there are no software tools or software libraries supporting all of them. This complicates the management of molecular network layouts and hinders their reuse and extension. In this paper, we present a high-level overview of the layout formats in systems biology, focusing on their commonalities and differences, review their support in existing software tools, libraries and repositories and finally introduce a new conversion module within the MINERVA platform. The module is available via a REST API and offers, besides the ability to convert between layout-aware systems biology formats, the possibility to export layouts into several graphical formats. The module enables conversion of very large networks with thousands of elements, such as disease maps or metabolic reconstructions, rendering it widely applicable in systems biology.", "date": "2019-07-10T00:00:00Z", "citationCount": 15, "authors": [ { "name": "Hoksza D." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Hasenauer J." }, { "name": "Schneider R." } ], "journal": "Briefings in Bioinformatics" } }, { "doi": "10.1089/big.2015.0057", "pmid": "27441714", "pmcid": "PMC4932659", "type": [ "Usage" ], "version": "10.0", "note": null, "metadata": { "title": "Integration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases", "abstract": "Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services - tranSMART, a Galaxy Server, and a MINERVA platform - are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and disease-related mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data.", "date": "2016-06-01T00:00:00Z", "citationCount": 38, "authors": [ { "name": "Satagopam V." }, { "name": "Gu W." }, { "name": "Eifes S." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Gebel S." }, { "name": "Barbosa-Silva A." }, { "name": "Balling R." }, { "name": "Schneider R." } ], "journal": "Big Data" } }, { "doi": "10.1016/j.envpol.2019.04.005", "pmid": "30991279", "pmcid": null, "type": [], "version": "13.1.1", "note": null, "metadata": { "title": "Genes associated with Parkinson's disease respond to increasing polychlorinated biphenyl levels in the blood of healthy females", "abstract": "Polychlorinated biphenyls (PCBs) are a class of widespread environmental pollutants, commonly found in human blood, that have been suggested to be linked to the occurrence of sporadic Parkinson's disease (PD). It has been reported that some non-coplanar PCBs accumulate in the brains of female PD patients. To improve our understanding of the association between PCB exposure and PD risk we have applied whole transcriptome gene expression analysis in blood cells from 594 PCB-exposed subjects (369 female, 225 male). Interestingly, we observe that in females, blood levels of non-coplanar PCBs appear to be associated with expression levels of PD-specific genes. However, no such association was detected in males. Among the 131 PD-specific genes affected, 39 have been shown to display similar changes in expression levels in the substantia nigra of deceased PD patients. Especially among the down-regulated genes, transcripts of genes involved in neurotransmitter vesicle-related functions were predominant. Capsule: Plasma PCB levels are associated with gene expression changes in females only, resulting in brain-related genes changing in blood cells of healthy individuals exposed to PCBs.", "date": "2019-07-01T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Bohler S." }, { "name": "Krauskopf J." }, { "name": "Espin-Perez A." }, { "name": "Gebel S." }, { "name": "Palli D." }, { "name": "Rantakokko P." }, { "name": "Kiviranta H." }, { "name": "Kyrtopoulos S.A." }, { "name": "Balling R." }, { "name": "Kleinjans J." } ], "journal": "Environmental Pollution" } } ], "credit": [], "owner": "mjostaszewski", "additionDate": "2019-08-26T14:34:55Z", "lastUpdate": "2025-04-14T09:01:54.711218Z", "editPermission": { "type": "group", "authors": [ "sascha.herzinger" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "OpenCloning", "description": "An Open-Source web application to plan and document cloning and genome engineering", "homepage": "https://opencloning.org/", "biotoolsID": "opencloning", "biotoolsCURIE": "biotools:opencloning", "version": [], "otherID": [], "relation": [ { "biotoolsID": "pydna", "type": "uses" }, { "biotoolsID": "biopython", "type": "uses" }, { "biotoolsID": "primer3", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0492", "term": "Multiple sequence alignment" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0491", "term": "Pairwise sequence alignment" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3095", "term": "Nucleic acid design" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0365", "term": "Restriction digest" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0230", "term": "Sequence generation" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3180", "term": "Sequence assembly validation" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3203", "term": "Chromatogram visualisation" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0573", "term": "Map drawing" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3925", "term": "Network visualisation" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0564", "term": "Sequence visualisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web API", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3912", "term": "Genetic engineering" }, { "uri": "http://edamontology.org/topic_3047", "term": "Molecular biology" }, { "uri": "http://edamontology.org/topic_3895", "term": "Synthetic biology" } ], "operatingSystem": [], "language": [ "Python", "JavaScript" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "UK" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/manulera/OpenCloning", "type": [ "Repository" ], "note": null }, { "url": "https://opencloning.org/", "type": [ "Service" ], "note": "Hosted web app" }, { "url": "https://github.com/manulera/OpenCloning_backend", "type": [ "Repository" ], "note": "Backend code" }, { "url": "https://github.com/manulera/OpenCloning_frontend", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/manulera/OpenCloning", "type": [ "General" ], "note": null } ], "publication": [], "credit": [ { "name": "Manuel Lera-Ramirez", "email": "manulera14@gmail.com", "url": "https://github.com/manulera", "orcidid": "https://orcid.org/0000-0002-8666-9746", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "manulera", "additionDate": "2025-04-11T20:52:47.895200Z", "lastUpdate": "2025-04-11T20:53:03.390161Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Protists Ribosomal Reference Database", "description": "The PR2 reference sequence database was initiated in 2010 in the frame of the BioMarks project from work that had developed in the previous ten years in the Plankton Group of the Station Biologique of Roscoff. It aims to provide a reference database of carefully annotated 18S rRNA sequences using nine unique taxonomic fields (from domain to species). At present, it contains over 240,000 sequences. Although it focuses on protists, it also contains sequences from metazoa, fungi and plants as well a limited set of 16S sequences from plastids and bacteria. Several metadata fields are available for many sequences, including geo-localisation, whether it originates from a culture or a natural sample, host type etc… The annotation of PR2 is performed by experts from each taxonomic groups.", "homepage": "https://app.pr2-database.org/", "biotoolsID": "pr2-reference", "biotoolsCURIE": "biotools:pr2-reference", "version": [ "5.1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Database portal", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_4038", "term": "Metabarcoding" } ], "operatingSystem": [], "language": [ "R" ], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/pr2database/pr2database/releases", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/pr2database/pr2database/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://pr2-database.org/", "type": [ "Other" ], "note": null } ], "download": [ { "url": "https://github.com/pr2database/pr2database/releases", "type": "Downloads page", "note": null, "version": "5.1.0" } ], "documentation": [ { "url": "https://pr2database.github.io/pr2database/articles/pr2database.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gks1160", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The Protist Ribosomal Reference database (PR2): A catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy", "abstract": "The interrogation of genetic markers in environmental meta-barcoding studies is currently seriously hindered by the lack of taxonomically curated reference data sets for the targeted genes. The Protist Ribosomal Reference database (PR2, http://ssu-rrna.org/) provides a unique access to eukaryotic small sub-unit (SSU) ribosomal RNA and DNA sequences, with curated taxonomy. The database mainly consists of nuclear-encoded protistan sequences. However, metazoans, land plants, macrosporic fungi and eukaryotic organelles (mitochondrion, plastid and others) are also included because they are useful for the analysis of high-troughput sequencing data sets. Introns and putative chimeric sequences have been also carefully checked. Taxonomic assignation of sequences consists of eight unique taxonomic fields. In total, 136866 sequences are nuclear encoded, 45708 (36 501 mitochondrial and 9657 chloroplastic) are from organelles, the remaining being putative chimeric sequences. The website allows the users to download sequences from the entire and partial databases (including representative sequences after clustering at a given level of similarity). Different web tools also allow searches by sequence similarity. The presence of both rRNA and rDNA sequences, taking into account introns (crucial for eukaryotic sequences), a normalized eight terms ranked-taxonomy and updates of new GenBank releases were made possible by a long-term collaboration between experts in taxonomy and computer scientists. © The Author(s) 2012.", "date": "2013-01-01T00:00:00Z", "citationCount": 1456, "authors": [ { "name": "Guillou L." }, { "name": "Bachar D." }, { "name": "Audic S." }, { "name": "Bass D." }, { "name": "Berney C." }, { "name": "Bittner L." }, { "name": "Boutte C." }, { "name": "Burgaud G." }, { "name": "De Vargas C." }, { "name": "Decelle J." }, { "name": "Del Campo J." }, { "name": "Dolan J.R." }, { "name": "Dunthorn M." }, { "name": "Edvardsen B." }, { "name": "Holzmann M." }, { "name": "Kooistra W.H.C.F." }, { "name": "Lara E." }, { "name": "Le Bescot N." }, { "name": "Logares R." }, { "name": "Mahe F." }, { "name": "Massana R." }, { "name": "Montresor M." }, { "name": "Morard R." }, { "name": "Not F." }, { "name": "Pawlowski J." }, { "name": "Probert I." }, { "name": "Sauvadet A.-L." }, { "name": "Siano R." }, { "name": "Stoeck T." }, { "name": "Vaulot D." }, { "name": "Zimmermann P." }, { "name": "Christen R." } ], "journal": "Nucleic Acids Research" } } ], "credit": [], "owner": "vaulot", "additionDate": "2025-04-11T13:56:02.037873Z", "lastUpdate": "2025-04-11T14:01:09.249274Z", "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": "Cloud-based Workflow Manager (CloWM)", "description": "Data analysis in the life sciences often suffers from reproducibility, standardization and accessibility issues and these problems become even more severe with the escalating volume and complexity of data. While best-practice data analysis workflows try to tackle these challenges, many existing workflows still grapple with scalability issues, limited portability due to tight coupling with the execution environment and accessibility constraints arising from the absence of user-friendly interfaces. To overcome these issues, we created CloWM, a comprehensive cloud-based workflow management platform that allows the generic transformation of command-line driven workflows into user-friendly web-based services. CloWM offers the seamless integration of (1) scientific workflows written in the Nextflow DSL, (2) robust data storage, (3) a highly scalable compute layer for data-intensive analysis tasks and (4) a user-friendly interface.", "homepage": "https://clowm.bi.denbi.de", "biotoolsID": "clowm", "biotoolsCURIE": "biotools:clowm", "version": [], "otherID": [], "relation": [ { "biotoolsID": "sans", "type": "includes" } ], "function": [], "toolType": [ "Web API", "Web service", "Bioinformatics portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [], "language": [ "Python", "JavaScript" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://gitlab.ub.uni-bielefeld.de/cmg/clowm", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://clowm.bi.denbi.de/api/v1/openapi.json", "type": "API specification", "note": null, "version": null }, { "url": "https://gitlab.ub.uni-bielefeld.de/cmg/clowm", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://clowm.bi.denbi.de/api/v1/docs", "type": [ "API documentation" ], "note": null }, { "url": "https://clowm.bi.denbi.de/terms", "type": [ "Terms of use" ], "note": null } ], "publication": [ { "doi": "10.5281/zenodo.14039069", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Daniel Göbel", "email": "dgoebel@techfak.uni-bielefeld.de", "url": "https://ekvv.uni-bielefeld.de/pers_publ/publ/PersonDetail.jsp?personId=223066601", "orcidid": "https://orcid.org/0009-0009-9985-3823", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer", "Developer", "Primary contact" ], "note": null }, { "name": "Michael Beckstette", "email": "mbeckste@cebitec.uni-bielefeld.de", "url": null, "orcidid": "https://orcid.org/0000-0002-3707-1692", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Documentor" ], "note": null }, { "name": "Bielefeld University", "email": null, "url": "https://www.uni-bielefeld.de", "orcidid": null, "gridid": null, "rorid": "02hpadn98", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Genome Informatics", "email": null, "url": "https://gi.cebitec.uni-bielefeld.de", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "NFDI4Microbiota", "email": null, "url": "https://nfdi4microbiota.de", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [], "note": null } ], "owner": "dgoebel", "additionDate": "2025-04-09T13:19:17.715967Z", "lastUpdate": "2025-04-09T14:21:50.981521Z", "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": "MarineMetagenomeDB", "description": "MarineMetagenomeDB provides standardized and manually curated metadata for 11,449 marine metagenomes from SRA and MG-RAST. It enables users to search, filter, visualize, and download metadata through a web application equipped with quick and advanced search options, interactive map selection, and export tools. The database enhances data findability and reuse for comparative and large-scale meta-analyses in marine microbiome research.", "homepage": "https://webapp.ufz.de/marmdb/", "biotoolsID": "marinemetagenomedb", "biotoolsCURIE": "biotools:marinemetagenomedb", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" }, { "uri": "http://edamontology.org/topic_3837", "term": "Metagenomic sequencing" }, { "uri": "http://edamontology.org/topic_3277", "term": "Sample collections" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/s40793-022-00449-7", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "andersonavilasantos", "additionDate": "2025-04-08T12:40:26.806570Z", "lastUpdate": "2025-04-08T12:44:37.167081Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "AnimalAssociatedMetagenomeDB", "description": "The AnimalAssociatedMetagenomeDB (AAMDB) provides standardized and manually curated metadata for 10,885 non-human, animal-associated metagenomes collected from public repositories such as SRA and MG-RAST. It allows users to search, filter, visualize, and export metadata through an interactive web application featuring quick and advanced search options, geographic map-based selection, and support for raw data download. The tool facilitates the discovery and reuse of metagenomic data in biodiversity and microbiome studies.", "homepage": "https://webapp.ufz.de/aamdb/", "biotoolsID": "animalassociatedmetagenomedb", "biotoolsCURIE": "biotools:animalassociatedmetagenomedb", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3435", "term": "Standardisation and normalisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3837", "term": "Metagenomic sequencing" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" }, { "uri": "http://edamontology.org/topic_3277", "term": "Sample collections" } ], "operatingSystem": [], "language": [ "R" ], "license": null, "collectionID": [ "NFDI4Microbiota" ], "maturity": null, "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/s42523-023-00267-3", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "andersonavilasantos", "additionDate": "2025-04-08T12:16:36.396210Z", "lastUpdate": "2025-04-08T12:38:13.124276Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "RAMClustR", "description": "A feature clustering algorithm for non-targeted mass spectrometric metabolomics data.", "homepage": "https://github.com/cbroeckl/RAMClustR", "biotoolsID": "ramclustr", "biotoolsCURIE": "biotools:ramclustr", "version": [ "1.2.2", "1.3.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3557", "term": "Imputation" }, { "uri": "http://edamontology.org/operation_3435", "term": "Standardisation and normalisation" }, { "uri": "http://edamontology.org/operation_3432", "term": "Clustering" }, { "uri": "http://edamontology.org/operation_3465", "term": "Correlation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_2333", "term": "Binary format" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] }, { "data": { "uri": "http://edamontology.org/data_1270", "term": "Feature table" }, "format": [ { "uri": "http://edamontology.org/format_2333", "term": "Binary format" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] }, { "data": { "uri": "http://edamontology.org/data_3113", "term": "Sample annotation" }, "format": [ { "uri": "http://edamontology.org/format_2333", "term": "Binary format" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" } ], "operatingSystem": [], "language": [ "R" ], "license": "GPL-2.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://umsa.cerit-sc.cz/root?tool_id=toolshed.g2.bx.psu.edu/repos/recetox/ramclustr/ramclustr/1.3.0+galaxy0", "type": [ "Galaxy service" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1021/ac501530d", "pmid": "24927477", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "RAMClust: A novel feature clustering method enables spectral-matching-based annotation for metabolomics data", "abstract": "Metabolomic data are frequently acquired using chromatographically coupled mass spectrometry (MS) platforms. For such datasets, the first step in data analysis relies on feature detection, where a feature is defined by a mass and retention time. While a feature typically is derived from a single compound, a spectrum of mass signals is more a more-accurate representation of the mass spectrometric signal for a given metabolite. Here, we report a novel feature grouping method that operates in an unsupervised manner to group signals from MS data into spectra without relying on predictability of the in-source phenomenon. We additionally address a fundamental bottleneck in metabolomics, annotation of MS level signals, by incorporating indiscriminant MS/MS (idMS/MS) data implicitly: feature detection is performed on both MS and idMS/MS data, and feature-feature relationships are determined simultaneously from the MS and idMS/MS data. This approach facilitates identification of metabolites using in-source MS and/or idMS/MS spectra from a single experiment, reduces quantitative analytical variation compared to single-feature measures, and decreases false positive annotations of unpredictable phenomenon as novel compounds. This tool is released as a freely available R package, called RAMClustR, and is sufficiently versatile to group features from any chromatographic-spectrometric platform or feature-finding software. © 2014 American Chemical Society.", "date": "2014-07-15T00:00:00Z", "citationCount": 201, "authors": [ { "name": "Broeckling C.D." }, { "name": "Afsar F.A." }, { "name": "Neumann S." }, { "name": "Ben-Hur A." }, { "name": "Prenni J.E." } ], "journal": "Analytical Chemistry" } } ], "credit": [ { "name": "Corey Broeckling", "email": "Corey.Broeckling@ColoState.EDU", "url": null, "orcidid": "https://orcid.org/0000-0002-6158-827X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "recetox-specdatri", "additionDate": "2021-09-22T08:33:22.081093Z", "lastUpdate": "2025-04-02T11:37:27.390711Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "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 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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. 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DeepAnnotation predicts phenotypes from comprehensive multi-omics functional annotations with interpretable deep learning framework.", "homepage": "https://github.com/mawenlong2016/DeepAnnotation", "biotoolsID": "deepannotation", "biotoolsCURIE": "biotools:deepannotation", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool", "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" } ], "operatingSystem": [], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/mawenlong2016/DeepAnnotation", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/mawenlong2016/DeepAnnotation", "type": "Downloads page", "note": "GitHub repository", "version": null } ], "documentation": [], "publication": [], "credit": [], "owner": "mawenlong2025", "additionDate": "2025-03-22T00:35:21.183948Z", "lastUpdate": "2025-03-22T00:35:21.186342Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "European Health Research Data and Sample Catalogue", "description": "A collaborative effort to integrate the catalogues of diverse EU research projects and networks to accelerate reuse and improve citizens health.", "homepage": "https://data-catalogue.molgeniscloud.org/", "biotoolsID": "molgenis_european_health_research_data_and_sample_catalogue", "biotoolsCURIE": "biotools:molgenis_european_health_research_data_and_sample_catalogue", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Database portal" ], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1055/s-0042-1742522", "pmid": "36463884", "pmcid": "PMC9719789", "type": [], "version": null, "note": null, "metadata": { "title": "Towards an Interoperable Ecosystem of Research Cohort and Real-world Data Catalogues Enabling Multi-center Studies", "abstract": "Objectives: Existing individual-level human data cover large populations on many dimensions such as lifestyle, demography, laboratory measures, clinical parameters, etc. Recent years have seen large investments in data catalogues to FAIRify data descriptions to capitalise on this great promise, i.e. make catalogue contents more Findable, Accessible, Interoperable and Reusable. However, their valuable diversity also created heterogeneity, which poses challenges to optimally exploit their richness. Methods: In this opinion review, we analyse catalogues for human subject research ranging from cohort studies to surveillance, administrative and healthcare records. Results: We observe that while these catalogues are heterogeneous, have various scopes, and use different terminologies, still the underlying concepts seem potentially harmonizable. We propose a unified framework to enable catalogue data sharing, with catalogues of multi-center cohorts nested as a special case in catalogues of real-world data sources. Moreover, we list recommendations to create an integrated community of metadata catalogues and an open catalogue ecosystem to sustain these efforts and maximise impact. Conclusions: We propose to embrace the autonomy of motivated catalogue teams and invest in their collaboration via minimal standardisation efforts such as clear data licensing, persistent identifiers for linking same records between catalogues, minimal metadata 'common data elements' using shared ontologies, symmetric architectures for data sharing (push/pull) with clear provenance tracks to process updates and acknowledge original contributors. And most importantly, we encourage the creation of environments for collaboration and resource sharing between catalogue developers, building on international networks such as OpenAIRE and research data alliance, as well as domain specific ESFRIs such as BBMRI and ELIXIR.", "date": "2022-12-04T00:00:00Z", "citationCount": 9, "authors": [ { "name": "Swertz M." }, { "name": "Van Enckevort E." }, { "name": "Oliveira J.L." }, { "name": "Fortier I." }, { "name": "Bergeron J." }, { "name": "Thurin N.H." }, { "name": "Hyde E." }, { "name": "Kellmann A." }, { "name": "Pahoueshnja R." }, { "name": "Sturkenboom M." }, { "name": "Cunnington M." }, { "name": "Nybo Andersen A.-M." }, { "name": "Marcon Y." }, { "name": "Goncalves G." }, { "name": "Gini R." } ], "journal": "Yearbook of Medical Informatics" } } ], "credit": [], "owner": "EleanorHyde", "additionDate": "2025-03-11T14:55:53.492167Z", "lastUpdate": "2025-03-19T15:08:24.036904Z", "editPermission": { "type": "group", "authors": [ "mswertz", 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Next Generation Sequencing studies are constantly increasing the number of protein sequences. Given the huge disproportion between protein sequences and structures, there is a need for tools suited to annotate the effect of mutations starting from protein sequence without relying on the structure. Here, we describe INPS, a novel approach for annotating the effect of non-synonymous mutations on the protein stability from its sequence. INPS is based on SVM regression and it is trained to predict the thermodynamic free energy change upon single-point variations in protein sequences. Results: We show that INPS performs similarly to the state-of-the-art methods based on protein structure when tested in cross-validation on a non-redundant dataset. INPS performs very well also on a newly generated dataset consisting of a number of variations occurring in the tumor suppressor protein p53. Our results suggest that INPS is a tool suited for computing the effect of non-synonymous polymorphisms on protein stability when the protein structure is not available. We also show that INPS predictions are complementary to those of the state-of-the-art, structure-based method mCSM. When the two methods are combined, the overall prediction on the p53 set scores significantly higher than those of the single methods.", "date": "2015-02-06T00:00:00Z", "citationCount": 111, "authors": [ { "name": "Fariselli P." }, { "name": "Martelli P.L." }, { "name": "Savojardo C." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bioinformatics/btw192", "pmid": "27153629", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "INPS-MD: A web server to predict stability of protein variants from sequence and structure", "abstract": "Motivation: Protein function depends on its structural stability. The effects of single point variations on protein stability can elucidate the molecular mechanisms of human diseases and help in developing new drugs. Recently, we introduced INPS, a method suited to predict the effect of variations on protein stability from protein sequence and whose performance is competitive with the available state-of-the-art tools. Results: In this article, we describe INPS-MD (Impact of Non synonymous variations on Protein Stability-Multi-Dimension), a web server for the prediction of protein stability changes upon single point variation from protein sequence and/or structure. Here, we complement INPS with a new predictor (INPS3D) that exploits features derived from protein 3D structure. INPS3D scores with Pearson's correlation to experimental ΔΔG values of 0.58 in cross validation and of 0.72 on a blind test set. The sequence-based INPS scores slightly lower than the structure-based INPS3D and both on the same blind test sets well compare with the state-of-the-art methods.", "date": "2016-08-15T00:00:00Z", "citationCount": 189, "authors": [ { "name": "Savojardo C." }, { "name": "Fariselli P." }, { "name": "Martelli P.L." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "https://www.biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Piero Fariselli", "email": "piero.fariselli@unito.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Castrense Savojardo", "email": "savojard@biocomp.unibo.it", "url": "http://biocomp.unibo.it/savojard/", "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2016-05-04T15:36:53Z", "lastUpdate": "2025-03-19T15:01:04.207003Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-ITA-BOLOGNA", "savo", "Pub2Tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "chewBBaca", "description": "chewBBACA is a software suite for the creation and evaluation of core genome and whole genome MultiLocus Sequence Typing (cg/wgMLST) schemas and results.", "homepage": "https://github.com/B-UMMI/chewBBACA", "biotoolsID": "chewbbaca", "biotoolsCURIE": "biotools:chewbbaca", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3840", "term": "Multilocus sequence typing" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://chewbbaca.readthedocs.io/en/latest/index.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1099/MGEN.0.000166", "pmid": "29543149", "pmcid": "PMC5885018", "type": [], "version": null, "note": null, "metadata": { "title": "chewBBACA: A complete suite for gene-by-gene schema creation and strain identification", "abstract": "Gene-by-gene approaches are becoming increasingly popular in bacterial genomic epidemiology and outbreak detection. However, there is a lack of open-source scalable software for schema definition and allele calling for these methodologies. The chewBBACA suite was designed to assist users in the creation and evaluation of novel whole-genome or core-genome gene-by-gene typing schemas and subsequent allele calling in bacterial strains of interest. chewBBACA performs the schema creation and allele calls on complete or draft genomes resulting from de novo assemblers. The chewBBACA software uses Python 3.4 or higher and can run on a laptop or in high performance clusters making it useful for both small laboratories and large reference centers. ChewBBACA is available at https://github.com/B-UMMI/chewBBACA.", "date": "2018-03-01T00:00:00Z", "citationCount": 276, "authors": [ { "name": "Silva M." }, { "name": "Machado M.P." }, { "name": "Silva D.N." }, { "name": "Rossi M." }, { "name": "Moran-Gilad J." }, { "name": "Santos S." }, { "name": "Ramirez M." }, { "name": "Carrico J.A." } ], "journal": "Microbial genomics" } } ], "credit": [], "owner": "EngyNasr", "additionDate": "2025-03-17T15:56:34.552871Z", "lastUpdate": "2025-03-19T14:47:22.843193Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "pyMLST", "description": "A Python Mlst Local Search Tool. The input can be (i) an assembler-generated draft genome, (ii) the direct raw data, or (iii) other genomes stored in the sequence database.", "homepage": "https://github.com/bvalot/pyMLST", "biotoolsID": "pymlst", "biotoolsCURIE": "biotools:pymlst", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3840", "term": "Multilocus sequence typing" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" } ], "operatingSystem": [], "language": [ "Python" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://pymlst.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1099/mgen.0.001126", "pmid": "37966168", "pmcid": "PMC10711306", "type": [], "version": null, "note": null, "metadata": { "title": "Introduction and benchmarking of pyMLST: open-source software for assessing bacterial clonality using core genome MLST", "abstract": "Core genome multilocus sequence typing (cgMLST) has gained in popularity for bacterial typing since whole-genome sequencing (WGS) has become affordable. We introduce here pyMLST, a new complete, stand-alone, free and open source pipeline for cgMLST analysis. pyMLST can create or import a core genome database. For each gene, the first allele is aligned against the bacterial genome of interest using BLAT. Incomplete genes are aligned using MAFT. All data are stored in a SQLite database. pyMLST accepts assembly genomes or raw data (with the option pyMLST-KMA) as input. To evaluate our new tool, we selected three genome collections of major bacterial pathogens (Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus) and compared them with pyMLST, pyMLST-KMA, ChewBBACA, SeqSphere and the variant calling approach. We compared the sensitivity, precision and false-positive rate for each method with those of the variant calling approach. Minimal spanning trees were generated with each type of software to evaluate their interest in the context of a bacterial outbreak. We found that pyMLST-KMA is a convenient screening method to avoid assembling large bacterial collections. Our data showed that pyMLST (free, open source, available in Galaxy and pipeline ready) performed similarly to the commercial SeqSphere and performed better than ChewBBACA and pyMLST-KMA.", "date": "2023-11-01T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Biguenet A." }, { "name": "Bordy A." }, { "name": "Atchon A." }, { "name": "Hocquet D." }, { "name": "Valot B." } ], "journal": "Microbial Genomics" } } ], "credit": [], "owner": "EngyNasr", "additionDate": "2025-03-17T16:13:12.338060Z", "lastUpdate": "2025-03-19T14:40:54.280165Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "pisad", "description": "Phsaed Intraspecies Sample Anomalies Detection tool", "homepage": "https://github.com/ZhantianXu/PISAD", "biotoolsID": "pisad", "biotoolsCURIE": "biotools:pisad", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [], "operatingSystem": [], "language": [], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "zhantianxu", "additionDate": "2025-03-18T13:10:47.976399Z", "lastUpdate": "2025-03-19T14:27:51.531329Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DDGemb", "description": "Predicting the impact of mutations on protein stability from sequence using protein language models", "homepage": "https://ddgemb.biocomp.unibo.it", "biotoolsID": "ddgemb", "biotoolsCURIE": "biotools:ddgemb", "version": [ "1" ], "otherID": [], "relation": [], "function": [ { "operation": [], "input": [ { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0130", "term": "Protein folding, stability and design" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Italy" ], "elixirCommunity": [ "Rare Diseases", "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "https://ddgemb.biocomp.unibo.it/help/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btaf019", "pmid": "39799516", "pmcid": "PMC11783275", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "DDGemb: predicting protein stability change upon single- and multi-point variations with embeddings and deep learning", "abstract": "Motivation: The knowledge of protein stability upon residue variation is an important step for functional protein design and for understanding how protein variants can promote disease onset. Computational methods are important to complement experimental approaches and allow a fast screening of large datasets of variations. Results: In this work, we present DDGemb, a novel method combining protein language model embeddings and transformer architectures to predict protein ΔΔG upon both single- and multi-point variations. DDGemb has been trained on a high-quality dataset derived from literature and tested on available benchmark datasets of single- and multi-point variations. DDGemb performs at the state of the art in both single- and multi-point variations.", "date": "2025-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Savojardo C." }, { "name": "Manfredi M." }, { "name": "Martelli P.L." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "https://www.biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer", "Developer", "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2025-03-17T14:56:35.753220Z", "lastUpdate": "2025-03-17T15:08:51.796427Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "INPS", "description": "Predicting the impact of mutations on protein stability from sequence", "homepage": "https://inpsmd.biocomp.unibo.it", "biotoolsID": "inps", "biotoolsCURIE": "biotools:inps", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [] } ], "note": "Prediction of the impact of non-synonymous polymorphisms on protein stability", "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0130", "term": "Protein folding, stability and design" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://inpsmd.biocomp.unibo.it/help", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btv291", "pmid": "25957347", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "INPS: Predicting the impact of non-synonymous variations on protein stability from sequence", "abstract": "Motivation: A tool for reliably predicting the impact of variations on protein stability is extremely important for both protein engineering and for understanding the effects of Mendelian and somatic mutations in the genome. Next Generation Sequencing studies are constantly increasing the number of protein sequences. Given the huge disproportion between protein sequences and structures, there is a need for tools suited to annotate the effect of mutations starting from protein sequence without relying on the structure. Here, we describe INPS, a novel approach for annotating the effect of non-synonymous mutations on the protein stability from its sequence. INPS is based on SVM regression and it is trained to predict the thermodynamic free energy change upon single-point variations in protein sequences. Results: We show that INPS performs similarly to the state-of-the-art methods based on protein structure when tested in cross-validation on a non-redundant dataset. INPS performs very well also on a newly generated dataset consisting of a number of variations occurring in the tumor suppressor protein p53. Our results suggest that INPS is a tool suited for computing the effect of non-synonymous polymorphisms on protein stability when the protein structure is not available. We also show that INPS predictions are complementary to those of the state-of-the-art, structure-based method mCSM. When the two methods are combined, the overall prediction on the p53 set scores significantly higher than those of the single methods.", "date": "2015-02-06T00:00:00Z", "citationCount": 111, "authors": [ { "name": "Fariselli P." }, { "name": "Martelli P.L." }, { "name": "Savojardo C." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bioinformatics/btw192", "pmid": "27153629", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "INPS-MD: A web server to predict stability of protein variants from sequence and structure", "abstract": "Motivation: Protein function depends on its structural stability. The effects of single point variations on protein stability can elucidate the molecular mechanisms of human diseases and help in developing new drugs. Recently, we introduced INPS, a method suited to predict the effect of variations on protein stability from protein sequence and whose performance is competitive with the available state-of-the-art tools. Results: In this article, we describe INPS-MD (Impact of Non synonymous variations on Protein Stability-Multi-Dimension), a web server for the prediction of protein stability changes upon single point variation from protein sequence and/or structure. Here, we complement INPS with a new predictor (INPS3D) that exploits features derived from protein 3D structure. INPS3D scores with Pearson's correlation to experimental ΔΔG values of 0.58 in cross validation and of 0.72 on a blind test set. The sequence-based INPS scores slightly lower than the structure-based INPS3D and both on the same blind test sets well compare with the state-of-the-art methods.", "date": "2016-08-15T00:00:00Z", "citationCount": 189, "authors": [ { "name": "Savojardo C." }, { "name": "Fariselli P." }, { "name": "Martelli P.L." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "http://www.biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact" ], "note": null }, { "name": "Piero Fariselli", "email": "piero.fariselli@unito.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2016-05-04T15:36:53Z", "lastUpdate": "2025-03-17T14:54:19.762674Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-ITA-BOLOGNA", "savo" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Raster extraction", "description": "This Python script provides functions to process raster files in chunks and extract values at specified coordinates using multiprocessing. 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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. Furthermore, we recount the most popular webtools and standalone applications performing gene coexpression analysis, with details on their methods, features and outputs.", "date": "2022-07-01T00:00:00Z", "citationCount": 9, "authors": [ { "name": "Zogopoulos V.L." }, { "name": "Saxami G." }, { "name": "Malatras A." }, { "name": "Papadopoulos K." }, { "name": "Tsotra I." }, { "name": "Iconomidou V.A." }, { "name": "Michalopoulos I." } ], "journal": "Biology" } }, { "doi": "10.1093/nar/gkl204", "pmid": "16845059", "pmcid": "PMC1538833", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Arabidopsis Co-expression Tool (ACT): Web server tools for microarray-based gene expression analysis", "abstract": "The Arabidopsis Co-expression Tool, ACT, ranks the genes across a large microarray dataset according to how closely their expression follows the expression of a query gene. 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": "PEP-FOLD4", "description": "PEP-FOLD4 is a fast and accurate structure prediction tool for peptides of up to 40 amino acids in aqueous solutions. Unlike many machine-learning approaches (e.g., AlphaFold2, TrRosetta, RaptorX), it integrates the Debye-Hückel formalism for charged side-chain interactions with a Mie potential for intramolecular forces. 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All repository content is covered by a non-commercial license agreement and may be used for non-commercial and internal research purposes only.", "version": null } ], "documentation": [ { "url": "https://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD4/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkad376", "pmid": "37166962", "pmcid": "PMC10320157", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "PEP-FOLD4: A pH-dependent force field for peptide structure prediction in aqueous solution", "abstract": "Accurate and fast structure prediction of peptides of less 40 amino acids in aqueous solution has many biological applications, but their conformations are pH-and salt concentration-dependent. In this work, we present PEP-FOLD4 which goes one step beyond many machine-learning approaches, such as AlphaFold2, TrRosetta and RaptorX. Adding the Debye-Hueckel formalism for charged-charged side chain interactions to a Mie formalism for all intramolecular (backbone and side chain) interactions, PEP-FOLD4, based on a coarse-grained representation of the peptides, performs as well as machine-learning methods on well-structured peptides, but displays significant improvements for poly-charged peptides. PEP-FOLD4 is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD4. This server is free and there is no login requirement.", "date": "2023-07-05T00:00:00Z", "citationCount": 39, "authors": [ { "name": "Rey J." }, { "name": "Murail S." }, { "name": "De Vries S." }, { "name": "Derreumaux P." }, { "name": "Tuffery P." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Julien Rey", "email": "julien.rey@u-paris.fr", "url": null, "orcidid": "https://orcid.org/0000-0002-3050-511X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Support", "Developer", "Primary contact" ], "note": null }, { "name": "Samuel Murail", "email": "samuel.muriail@u-paris.fr", "url": null, "orcidid": "https://orcid.org/0000-0002-3842-5333", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Sjoerd de Vries", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-7701-3454", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Philippe Derreumaux", "email": "philippe.derreumaux@ibpc.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Pierre Tufféry", "email": "pierre.tuffery@inserm.fr", "url": null, "orcidid": "https://orcid.org/0000-0003-1033-9895", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "nchevrollier", "additionDate": "2025-03-04T16:25:28.372680Z", "lastUpdate": "2025-03-05T16:21:19.399517Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "LipidOne 2.2", "description": "User-friendly lipidomic data analysis tool for a deeper interpretation in a systems biology scenario", "homepage": "https://lipidone.eu/", "biotoolsID": "lipidone_2.2", "biotoolsCURIE": "biotools:lipidone_2.2", "version": [ "2.2" ], "otherID": [], "relation": [ { "biotoolsID": "lipidone", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3926", "term": "Pathway visualisation" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2939", "term": "Principal component visualisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_0153", "term": "Lipidomics" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3473", "term": "Data mining" }, { "uri": "http://edamontology.org/topic_3360", "term": "Biomarkers" } ], "operatingSystem": [], "language": [], "license": "Freeware", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [ "Metabolomics" ], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1002/cpz1.70009", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "LipidOne 2.0: A Web Tool for Discovering Biological Meanings Hidden in Lipidomic Data", "abstract": "LipidOne 2.0 (https://lipidone.eu) is a new web bioinformatic tool for the analysis of lipidomic data. It facilitates the exploration of the three structural levels of lipids: classes, molecular species, and lipid building blocks (acyl, alkyl, or alkenes chains). The tool's flexibility empowers users to seamlessly include or exclude experimental groups and lipid classes at any stage of the analysis. LipidOne 2.0 offers a range of mono- and multivariate statistical analyses, specifically tailored to each structural level. This includes a novel lipid biomarker identification function, integrating four diverse statistical parameters. LipidOne 2.0 incorporates Lipid Pathway analysis across all three structural levels of lipids. Users can identify lipid-involved reactions through case-control comparisons, generating lists of genes/enzymes and their activation states based on Z scores. Accessible without the need for registration, LipidOne 2.0 provides a user-friendly and efficient platform for exploring and analyzing lipidomic data. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Dataset preparation for LipidOne 2.0. Support Protocol: Lipid nomenclature from spectrometric experiments. Basic Protocol 2: Uploading a dataset into LipidOne 2.0. Basic Protocol 3: Data mining of lipidomic dataset by LipidOne 2.0.", "date": "2024-09-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Alabed H.B.R." }, { "name": "Mancini D.F." }, { "name": "Buratta S." }, { "name": "Calzoni E." }, { "name": "Giacomo D.D." }, { "name": "Emiliani C." }, { "name": "Martino S." }, { "name": "Urbanelli L." }, { "name": "Pellegrino R.M." } ], "journal": "Current Protocols" } } ], "credit": [ { "name": "Roberto Maria Pellegrino", "email": "roberto.pellegrino@unipg.it", "url": "https://lipidone.eu/", "orcidid": "https://orcid.org/0000-0001-5594-383X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "RobertoMaria", "additionDate": "2025-03-05T11:34:50.555785Z", "lastUpdate": "2025-03-05T11:34:50.558190Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Coxmos", "description": "The Coxmos (Cox MultiBlock Survival) R package is an end-to-end pipeline designed for the study of survival analysis for high dimensional data. Updating classical methods and adding new ones based on sPLS technologies. Furthermore, includes multiblock functions to work with multiple sets of information to improve survival accuracy.", "homepage": "https://CRAN.R-project.org/package=Coxmos", "biotoolsID": "coxmos", "biotoolsCURIE": "biotools:coxmos", "version": [ "1.1.1" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_4021", "term": "Multiomics" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "CC-BY-4.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/BiostatOmics/Coxmos/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/BiostatOmics/Coxmos", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://cran.r-project.org/web/packages/Coxmos/Coxmos.pdf", "type": [ "User manual" ], "note": null }, { "url": "https://cran.r-project.org/web/packages/Coxmos/vignettes/Coxmos-pipeline.html", "type": [ "Quick start guide" ], "note": "Single-Omic Analysis" }, { "url": "https://cran.r-project.org/web/packages/Coxmos/vignettes/Coxmos-MO-pipeline.html", "type": [ "Quick start guide" ], "note": "Multi-Omic Analysis" } ], "publication": [], "credit": [ { "name": "Pedro Salguero García", "email": "pedrosalguerog@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0002-1879-3374", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer", "Developer" ], "note": null } ], "owner": "biostatomics1", "additionDate": "2025-03-03T14:20:54.340271Z", "lastUpdate": "2025-03-04T15:20:02.818403Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MORE", "description": "MORE (Multi-Omics REgulation) is an R package for the application of Partial Least Squares (PLS) or Multiple Linear Regression (MLR) models with Elastic Net or Iterative Sparse Group Lasso (ISGL) regularizations to multi-omics data. The MORE method applies MLRs or PLS to model a target omic expression as a function of experimental variables, such as diseases or treatments, and the potential regulators of that given target feature. The aim is to obtain specific candidate regulators for the biological system under study.", "homepage": "https://github.com/BiostatOmics/MORE", "biotoolsID": "more", "biotoolsCURIE": "biotools:more", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3927", "term": "Network analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_4021", "term": "Multiomics" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Other", "R" ], "license": "GPL-2.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/BiostatOmics/MORE", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1101/2024.01.25.577162", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": "This is a preprint available at bioRxiv. When the paper is published the link wil be updated.", "metadata": null } ], "credit": [ { "name": "Maider Aguerralde Martin", "email": "magumar2@posgrado.upv.es", "url": null, "orcidid": "https://orcid.org/0000-0001-9266-8689", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer" ], "note": null } ], "owner": "biostatomics1", "additionDate": "2025-03-03T11:35:43.315630Z", "lastUpdate": "2025-03-04T15:19:11.815695Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MultiPower", "description": "The MultiPower R method performs statistical power studies for multi-omics experiments, and is designed to assist users in experimental design as well as in the evaluation of already-generated multi-omics datasets.", "homepage": "https://github.com/ConesaLab/MultiPower", "biotoolsID": "multipower", "biotoolsCURIE": "biotools:multipower", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_4031", "term": "Power test" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_4021", "term": "Multiomics" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "GPL-2.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/ConesaLab/MultiPower", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/ConesaLab/MultiPower/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/ConesaLab/MultiPower/blob/master/MultiPowerUsersGuide_v2.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1038/s41467-020-16937-8", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Harmonization of quality metrics and power calculation in multi-omic studies", "abstract": "Multi-omic studies combine measurements at different molecular levels to build comprehensive models of cellular systems. The success of a multi-omic data analysis strategy depends largely on the adoption of adequate experimental designs, and on the quality of the measurements provided by the different omic platforms. However, the field lacks a comparative description of performance parameters across omic technologies and a formulation for experimental design in multi-omic data scenarios. Here, we propose a set of harmonized Figures of Merit (FoM) as quality descriptors applicable to different omic data types. Employing this information, we formulate the MultiPower method to estimate and assess the optimal sample size in a multi-omics experiment. MultiPower supports different experimental settings, data types and sample sizes, and includes graphical for experimental design decision-making. MultiPower is complemented with MultiML, an algorithm to estimate sample size for machine learning classification problems based on multi-omic data.", "date": "2020-12-01T00:00:00Z", "citationCount": 54, "authors": [ { "name": "Tarazona S." }, { "name": "Balzano-Nogueira L." }, { "name": "Gomez-Cabrero D." }, { "name": "Schmidt A." }, { "name": "Imhof A." }, { "name": "Hankemeier T." }, { "name": "Tegner J." }, { "name": "Westerhuis J.A." }, { "name": "Conesa A." } ], "journal": "Nature Communications" } } ], "credit": [ { "name": "Sonia Tarazona", "email": "sotacam@eio.upv.es", "url": null, "orcidid": "https://orcid.org/0000-0001-5346-1407", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer" ], "note": null } ], "owner": "biostatomics1", "additionDate": "2025-03-03T15:06:10.867996Z", "lastUpdate": "2025-03-04T15:16:47.048391Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MOSim", "description": "MOSim (Multi-Omics Simulation) package simulates multi-omic experiments that mimic regulatory mechanisms within the cell, allowing flexible experimental design including time course and multiple groups.", "homepage": "https://bioconductor.org/packages/release/bioc/html/MOSim.html", "biotoolsID": "mosim", "biotoolsCURIE": "biotools:mosim", "version": [ "2.2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_4021", "term": "Multiomics" }, { "uri": "http://edamontology.org/topic_3524", "term": "Simulation experiment" }, { "uri": "http://edamontology.org/topic_2269", "term": "Statistics and probability" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/ConesaLab/MOSim", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/ConesaLab/MOSim/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1101/421834", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": "This is a preprint accesible at bioRxiv. When the paper is published it will be updated", "metadata": null } ], "credit": [ { "name": "Sonia Tarazona", "email": "sotacam@eio.upv.es", "url": null, "orcidid": "https://orcid.org/0000-0001-5346-1407", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer" ], "note": null } ], "owner": "biostatomics1", "additionDate": "2025-03-03T13:46:56.613465Z", "lastUpdate": "2025-03-04T15:12:34.696650Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MetIDfyR", "description": "Open-Source R Package to Decipher Small-Molecule Drugs Metabolism Through High Resolution Mass Spectrometry.\n\nMetIDfyR is an open-source, cross-platform and versatile R script to predict and detect metabolites in mass spectrometry data (mzML) based on the raw formula of the drug of interest.", "homepage": "https://github.com/agnesbrnb/MetIDfyR", "biotoolsID": "metidfyr", "biotoolsCURIE": "biotools:metidfyr", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3803", "term": "Natural product identification" }, { "uri": "http://edamontology.org/operation_3454", "term": "Phasing" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3244", "term": "mzML" } ] }, { "data": { "uri": "http://edamontology.org/data_0846", "term": "Chemical formula" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [ { "uri": "http://edamontology.org/format_3604", "term": "SVG" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_3375", "term": "Drug metabolism" }, { "uri": "http://edamontology.org/topic_3370", "term": "Analytical chemistry" } ], "operatingSystem": [], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/agnesbrnb/MetIDfyR", "type": [ "Quick start guide", "Installation instructions", "Citation instructions" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.analchem.0c02281", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "MetIDfyR: An Open-Source R Package to Decipher Small-Molecule Drug Metabolism through High-Resolution Mass Spectrometry", "abstract": "With recent advances in analytical chemistry, liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS) has become an essential tool for metabolite discovery and detection. Even if most of the common drug transformations have already been extensively described, manual search of drug metabolites in LC-HRMS/MS datasets is still a common practice in toxicology laboratories, complicating metabolite discovery. Furthermore, the availability of free open-source software for metabolite discovery is still limited. In this article, we present MetIDfyR, an open-source and cross-platform R package for in silico drug phase I/II biotransformation prediction and mass-spectrometric data mining. MetIDfyR has proven its efficacy for advanced metabolite identification in semi-complex and complex mixtures in in vitro or in vivo drug studies and is freely available at github.com/agnesblch/MetIDfyR.", "date": "2020-10-06T00:00:00Z", "citationCount": 10, "authors": [ { "name": "Delcourt V." }, { "name": "Barnabe A." }, { "name": "Loup B." }, { "name": "Garcia P." }, { "name": "Andre F." }, { "name": "Chabot B." }, { "name": "Trevisiol S." }, { "name": "Moulard Y." }, { "name": "Popot M.-A." }, { "name": "Bailly-Chouriberry L." } ], "journal": "Analytical Chemistry" } } ], "credit": [], "owner": "agnesbarnabe", "additionDate": "2021-01-18T09:08:27Z", "lastUpdate": "2025-02-27T15:46:01.807140Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" } ] }