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{ "count": 3469, "next": "?page=2", "previous": null, "list": [ { "name": "BufferCalc", "description": "Web application for designing thermodynamically corrected monoprotic buffers used in biological systems, with corrections for the temperature and ionic strength.", "homepage": "http://phbuffers.org/BuffferCalc/Buffer.html", "biotoolsID": "buffercalc", "biotoolsCURIE": "biotools:buffercalc", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3438", "term": "Calculation" } ], "input": [], "output": [ { "data": { "uri": "http://edamontology.org/data_2531", "term": "Protocol" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3314", "term": "Chemistry" } ], "operatingSystem": [], "language": [ "Other" ], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/bioinformatics/4.4.487", "pmid": "3208185", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "A Macintosh hypercard stack for calculation of thermodynamically-corrected buffer recipes", "abstract": "This paper describes a stack for the Apple MacintoshlTM, HypercardTM environment that facilitates the calculation of a set of thermodynamically-corrected pH buffers. Presented in the familiar Macintosh mouse-based environment, the program allows comprehensive buffer design and gives the user full control of buffer species, temperature, ionic strength, pH and choice of counter-ion to maintain the ionic strength at a fixed value. Addition of new buffers to the stack is straightforward and the recipes that are generated, including the weights of the various components, can be displayed on the screen or saved to a disk file for subsequent printing. © 1988 IRL Press Limited.", "date": "1988-11-01T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Beynon R.J." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2025-05-09T13:44:22.905859Z", "lastUpdate": "2025-05-09T13:48:04.641670Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "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": "OpenMS", "description": "Open source library and a collection of tools and interfaces for the analysis of mass spectrometry data. Includes over 200 standalone (TOPP) tools that can be combined to a workflow with the integrated workflow editor TOPPAS. Raw and intermediate mass spectrometry data can be visualised with the included viewer TOPPView.", "homepage": "http://www.openms.de", "biotoolsID": "openms", "biotoolsCURIE": "biotools:openms", "version": [ "2.0.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3767", "term": "Protein identification" }, { "uri": "http://edamontology.org/operation_1812", "term": "Parsing" }, { "uri": "http://edamontology.org/operation_2409", "term": "Data handling" }, { "uri": "http://edamontology.org/operation_3628", "term": "Chromatographic alignment" }, { "uri": "http://edamontology.org/operation_3627", "term": "Mass spectra calibration" }, { "uri": "http://edamontology.org/operation_0335", "term": "Formatting" }, { "uri": "http://edamontology.org/operation_3630", "term": "Protein quantification" }, { "uri": "http://edamontology.org/operation_3633", "term": "Retention time prediction" }, { "uri": "http://edamontology.org/operation_0226", "term": "Annotation" }, { "uri": "http://edamontology.org/operation_3092", "term": "Protein feature detection" }, { "uri": "http://edamontology.org/operation_3705", "term": "Isotope-coded protein label" }, { "uri": "http://edamontology.org/operation_3634", "term": "Label-free quantification" }, { "uri": "http://edamontology.org/operation_3639", "term": "iTRAQ" }, { "uri": "http://edamontology.org/operation_3631", "term": "Peptide identification" }, { "uri": "http://edamontology.org/operation_3215", "term": "Peak detection" }, { "uri": "http://edamontology.org/operation_3694", "term": "Mass spectrum visualisation" }, { "uri": "http://edamontology.org/operation_3635", "term": "Labeled quantification" }, { "uri": "http://edamontology.org/operation_3359", "term": "Splitting" }, { "uri": "http://edamontology.org/operation_3214", "term": "Spectral analysis" }, { "uri": "http://edamontology.org/operation_3629", "term": "Deisotoping" }, { "uri": "http://edamontology.org/operation_3649", "term": "Target-Decoy" }, { "uri": "http://edamontology.org/operation_3023", "term": "Prediction and recognition (protein)" }, { "uri": "http://edamontology.org/operation_2424", "term": "Comparison" }, { "uri": "http://edamontology.org/operation_3435", "term": "Standardisation and normalisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3655", "term": "pepXML" }, { "uri": "http://edamontology.org/format_3248", "term": "mzQuantML" }, { "uri": "http://edamontology.org/format_3652", "term": "dta" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" }, { "uri": "http://edamontology.org/format_3747", "term": "protXML" }, { "uri": "http://edamontology.org/format_3764", "term": "idXML" }, { "uri": "http://edamontology.org/format_2549", "term": "OBO" }, { "uri": "http://edamontology.org/format_2332", "term": "XML" }, { "uri": 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All rights reserved.High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.", "date": "2016-08-30T00:00:00Z", "citationCount": 246, "authors": [ { "name": "Rost H.L." }, { "name": "Sachsenberg T." }, { "name": "Aiche S." }, { "name": "Bielow C." }, { "name": "Weisser H." }, { "name": "Aicheler F." }, { "name": "Andreotti S." }, { "name": "Ehrlich H.-C." }, { "name": "Gutenbrunner P." }, { "name": "Kenar E." }, { "name": "Liang X." }, { "name": "Nahnsen S." }, { "name": "Nilse L." }, { "name": "Pfeuffer J." }, { "name": "Rosenberger G." }, { "name": "Rurik M." }, { "name": "Schmitt U." }, { "name": "Veit J." }, { "name": "Walzer M." }, { "name": "Wojnar D." }, { "name": "Wolski W.E." }, { "name": "Schilling O." }, { "name": "Choudhary J.S." }, { "name": "Malmstrom L." }, { "name": "Aebersold R." }, { "name": "Reinert K." }, { "name": "Kohlbacher O." } ], "journal": "Nature Methods" } }, { "doi": "10.1007/978-1-60761-987-1_23", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "OpenMS and TOPP: open source software for LC-MS data analysis.", "abstract": "Proteomics experiments based on state-of-the-art mass spectrometry produce vast amounts of data, which cannot be analyzed manually. Hence, software is needed which is able to analyze the data in an automated fashion. The need for robust and reusable software tools triggered the development of libraries implementing different algorithms for the various analysis steps. OpenMS is such a software library and provides a wealth of data structures and algorithms for the analysis of mass spectrometric data. For users unfamiliar with programming, TOPP (\"The OpenMS Proteomics Pipeline\") offers a wide range of already implemented tools sharing the same interface and designed for a specific analysis task each. TOPP thus makes the sophisticated algorithms of OpenMS accessible to nonprogrammers. The individual TOPP tools can be strung together into pipelines for analyzing mass spectrometry-based experiments starting from the raw output of the mass spectrometer. These analysis pipelines can be constructed using a graphical editor. Even complex analytical workflows can thus be analyzed with ease.", "date": "2011-01-01T00:00:00Z", "citationCount": 65, "authors": [ { "name": "Bertsch A." }, { "name": "Gropl C." }, { "name": "Reinert K." }, { "name": "Kohlbacher O." } ], "journal": "Methods in molecular biology (Clifton, N.J.)" } } ], "credit": [ { "name": "ETH Zürich", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Eberhard-Karls-Universität Tübingen", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Freie Universität Berlin", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Center for Integrative Bioinformatics (CiBi)", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [], "note": null }, { "name": "cibi", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "General Mailinglist", "email": "open-ms-general@lists.sourceforge.net", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Support" ], "note": null }, { "name": "General Mailinglist", "email": "open-ms-general@lists.sourceforge.net", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Hannes Röst", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0003-0990-7488", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "samwein", "additionDate": "2016-01-19T16:39:56Z", "lastUpdate": "2025-04-30T11:39:30.251890Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "pyOpenMS", "description": "Python library for mass spectrometry, specifically for the analysis of proteomics and metabolomics data.", "homepage": "https://github.com/OpenMS/pyopenms-extra/blob/master/docs/source/index.rst", "biotoolsID": "pyOpenMS", "biotoolsCURIE": "biotools:pyOpenMS", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0601", "term": "Protein modifications" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/OpenMS/pyopenms-extra", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/OpenMS/pyopenms-extra/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://pyopenms.readthedocs.io", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.7287/PEERJ.PREPRINTS.27736", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Hannes L. 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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. 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It is possible to curate and annotate metabolic networks in a collaborative environment. 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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": "Longitools Exposome Toolbox", "description": "The LongITools toolbox is an open-source platform developed to support exposome research analysis. This cloud-based computational environment enables researchers to construct customized analytical platforms suited to their specific research requirements. The system provides a web-based interface that integrates various analytical resources, including statistical tools, computational pipelines, connections to external data repositories, and data visualization capabilities.", "homepage": "https://longitools.bsc.es/vre/", "biotoolsID": "longitools_exposome_toolbox", "biotoolsCURIE": "biotools:longitools_exposome_toolbox", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Web application", "Command-line tool", "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3376", "term": "Medicines research and development" } ], "operatingSystem": [], "language": [ "R", "Python", "PHP" ], "license": null, "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://longitools.bsc.es/vre/", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/inab/openVRE/tree/longitools", "type": [ "Quick start guide" ], "note": null } ], "publication": [], "credit": [ { "name": "Karim Lekadir", "email": "karim.lekadir@ub.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-9456-1612", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact" ], "note": null } ], "owner": "noussair", "additionDate": "2025-04-23T10:31:12.521148Z", "lastUpdate": "2025-04-23T10:31:21.719823Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "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": "compareMS2", "description": "compareMS2 is a tool for comparing sets of (tandem) mass spectra for clustering samples, molecular phylogenetics, identification of biological species or tissues, and quality control. compareMS2 currently consumes Mascot Generic Format, or MGF, and produces output in a variety of common image and distance matrix formats.", "homepage": "https://github.com/524D/compareMS2", "biotoolsID": "comparems2", "biotoolsCURIE": "biotools:comparems2", "version": [ "1.0", "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2424", "term": "Comparison" }, { "uri": "http://edamontology.org/operation_0567", "term": "Phylogenetic tree visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3651", "term": "MGF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3272", "term": "Species tree" }, "format": [ { "uri": "http://edamontology.org/format_3603", "term": "PNG" }, { "uri": "http://edamontology.org/format_3604", "term": "SVG" } ] }, { "data": { "uri": "http://edamontology.org/data_2855", "term": "Distance matrix" }, "format": [ { "uri": "http://edamontology.org/format_1991", "term": "mega" }, { "uri": "http://edamontology.org/format_1912", "term": "Nexus format" }, { "uri": "http://edamontology.org/format_1910", "term": "newick" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0084", "term": "Phylogeny" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C", "JavaScript" ], "license": "MIT", "collectionID": [ "ms-utils", "Proteomics" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Netherlands" ], "elixirCommunity": [ "Proteomics" ], "link": [ { "url": "https://github.com/524D/compareMS2", "type": [ "Repository" ], "note": null }, { "url": "https://www.ms-utils.org/compareMS2.html", "type": [ "Software catalogue" ], "note": null }, { "url": "https://research-software-directory.org/software/comparems2", "type": [ "Software catalogue" ], "note": null } ], "download": [ { "url": "http://www.ms-utils.org/compareMS2.c", "type": "Source code", "note": null, "version": "1.0" }, { "url": "http://www.ms-utils.org/compareMS2.html", "type": "Binaries", "note": null, "version": "1.0" }, { "url": "http://www.ms-utils.org/compareMS2.c", "type": "Source code", "note": null, "version": "1.0" }, { "url": "https://github.com/524D/compareMS2/tree/main/src", "type": "Source code", "note": null, "version": "2.0" }, { "url": "https://github.com/524D/compareMS2/tree/main", "type": "Binaries", "note": null, "version": "2.0" } ], "documentation": [ { "url": "http://www.ms-utils.org/compareMS2.html", "type": [ "General", "Command-line options" ], "note": null }, { "url": "https://github.com/524D/compareMS2", "type": [ "General", "User manual", "Command-line options", "Installation instructions" ], "note": null } ], "publication": [ { "doi": "10.1002/rcm.6162", "pmid": "22368051", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "Molecular phylogenetics by direct comparison of tandem mass spectra", "abstract": "Rationale: Molecular phylogenetics is the study of evolution and relatedness of organisms or genes. Mass spectrometry is used routinely for bacterial identification and has also been used for phylogenetic analysis, for instance from bone material. Unfortunately, only a small fraction of the acquired tandem mass spectra allow direct interpretation. Methods: We describe a new algorithm and software for molecular phylogenetics using pairwise comparisons of tandem mass spectra from enzymatically digested proteins. The spectra need not be annotated and all acquired data is used in the analysis. To demonstrate the method, we analyzed tryptic digests of sera from four great apes and two other primates. Results: The distribution of spectra dot products for thousands of tandem mass spectra collected from two samples provides a measure on the fraction of shared peptides between the two samples. When inverted, this becomes a distance metric. By pairwise comparison between species and averaging over four individuals per species, it was possible to reconstruct the unique correct phylogenetic tree for the great apes and other primates. Conclusions: The new method described here has several attractive features compared with existing methods, among them simplicity, the unbiased use of all acquired data rather than a small subset of spectra, and the potential use of heavily degraded proteins or proteins with a priori unknown modifications. © 2012 John Wiley & Sons, Ltd.", "date": "2012-04-15T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Palmblad M." }, { "name": "Deelder A.M." } ], "journal": "Rapid Communications in Mass Spectrometry" } }, { "doi": "10.1021/acs.jproteome.2c00457", "pmid": "36173614", "pmcid": "PMC9903320", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry Datasets", "abstract": "It has long been known that biological species can be identified from mass spectrometry data alone. Ten years ago, we described a method and software tool, compareMS2, for calculating a distance between sets of tandem mass spectra, as routinely collected in proteomics. This method has seen use in species identification and mixture characterization in food and feed products, as well as other applications. Here, we present the first major update of this software, including a new metric, a graphical user interface and additional functionality. The data have been deposited to ProteomeXchange with dataset identifier PXD034932.", "date": "2023-02-03T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Marissen R." }, { "name": "Varunjikar M.S." }, { "name": "Laros J.F.J." }, { "name": "Rasinger J.D." }, { "name": "Neely B.A." }, { "name": "Palmblad M." } ], "journal": "Journal of Proteome Research" } }, { "doi": "10.1021/acs.jproteome.1c00528", "pmid": "34523928", "pmcid": "PMC8491155", "type": [ "Review" ], "version": "2.0", "note": null, "metadata": { "title": "Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics Experiments in the Light of Proteomics", "abstract": "Science is full of overlooked and undervalued research waiting to be rediscovered. Proteomics is no exception. In this perspective, we follow the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing tryptic peptides across animal species. This pioneering work directly led to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics. In the decades following, proteins continued to provide essential clues on evolutionary history. While technology has continued to improve, contemporary proteomics has strayed from this larger biological context, rarely comparing species or asking how protein structure, function, and interactions have evolved. Here we recombine proteomics with molecular phylogenetics, highlighting the value of framing proteomic results in a larger biological context and how almost forgotten research, though technologically surpassed, can still generate new ideas and illuminate our work from a different perspective. Though it is infeasible to read all research published on a large topic, looking up older papers can be surprisingly rewarding when rediscovering a \"gem\"at the end of a long citation chain, aided by digital collections and perpetually helpful librarians. Proper literature study reduces unnecessary repetition and allows research to be more insightful and impactful by truly standing on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/) as dataset MSV000087993.", "date": "2021-10-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Neely B.A." }, { "name": "Palmblad M." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "lumc.nl", "email": null, "url": "https://www.lumc.nl", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Support" ], "note": null }, { "name": "Magnus Palmblad", "email": "magnus.palmblad@gmail.com", "url": "https://github.com/magnuspalmblad", "orcidid": "http://orcid.org/0000-0002-5865-8994", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact", "Documentor" ], "note": null }, { "name": "Rob Marissen", "email": null, "url": "https://github.com/524D", "orcidid": "https://orcid.org/0000-0002-1220-9173", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2016-04-15T11:52:42Z", "lastUpdate": "2025-04-16T14:22:04.957317Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "openVRE", "description": "The Open Virtual Research Environment is a general purpose analysis platform that can be tailored for domain specific analyses.", "homepage": "https://github.com/inab/openVRE/wiki", "biotoolsID": "openvre", "biotoolsCURIE": "biotools:openvre", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "mugvre", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3760", "term": "Service management" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Bioinformatics portal", "Workbench" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Linux" ], "language": [ "PHP", "Python", "JavaScript" ], "license": "Apache-2.0", "collectionID": [ "EUCAIM" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Spain" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/inab/openVRE", "type": "Source code", "note": null, "version": "1.0" } ], "documentation": [ { "url": "http://vre.multiscalegenomics.eu/help/starting.php", "type": [ "Quick start guide" ], "note": "Getting Started Guide" } ], "publication": [], "credit": [ { "name": "Laia Codó", "email": "laia.codo@bsc.es", "url": "https://www.bsc.es/codo-laia", "orcidid": "https://orcid.org/0000-0002-6797-8746", "gridid": "grid.10097.3f", "rorid": "05sd8tv96", "fundrefid": "10.13039/501100006433", "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "Senior Researcher at Barcelona Supercomputing Center. Lead of Trusted Research Environments and Cloud Computing at INB Lab." }, { "name": "Josep Lluís Gelpí", "email": "gelpi@ub.edu", "url": "https://webgrec.ub.edu/webpages/000011/ang/gelpi.ub.edu.html", "orcidid": "http://orcid.org/0000-0002-0566-7723", "gridid": "grid.5841.8", "rorid": "021018s57", "fundrefid": "10.13039/501100005774", "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Professor at University of Barcelona and Team Leader at BSC's INB Laboratory" } ], "owner": "gelpi@ub.edu", "additionDate": "2025-04-16T08:53:57.270825Z", "lastUpdate": "2025-04-16T08:53:57.280528Z", "editPermission": { "type": "group", "authors": [ "gelpi@ub.edu" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Exposome Maps", "description": "The Exposome Maps contain geospatially resolved data on environmental exposures (Exposome Surfaces), categorized into the following Exposome dimensions:\nBuilt Environment28 exposures related to:\n•\tGreen space\n•\tBlue space\n•\tGrey space\nFood Environment4 exposures related to:\n•\tFood landscape / healthy food index\nPhysico-Chemical Environment99 exposures related to:\n•\tAir pollution\n•\tBiodiversity\n•\tWeather conditions\n•\tLight intensity at night\n•\tNoise\n•\tPesticides\n•\tElectromagnetic fields\nSocial Environment70 exposures related to:\n•\tNeighbourhood socio-economic position\n•\tNeighbourhood Demographic surfaces and population characteristics\n•\tSocial capital\n•\tSecurity\n•\tMental health\n•\tProximity to facilities\n•\tEnergy use\n•\tLabour market", "homepage": "https://exposome.dataplatform.nl/", "biotoolsID": "exposome_maps", "biotoolsCURIE": "biotools:exposome_maps", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_4012", "term": "FAIR data" }, { "uri": "http://edamontology.org/topic_3855", "term": "Environmental sciences" } ], "operatingSystem": [], "language": [], "license": "Other", "collectionID": [ "EXPANSE", "EHEN" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Restricted access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://expanseproject.eu/", "type": [ "Other" ], "note": "Project information page" } ], "download": [], "documentation": [ { "url": "https://surfdrive.surf.nl/files/index.php/s/uqUORDrd428H2F9", "type": [ "User manual" ], "note": "Description of Environmental variables available through Exposome Maps" }, { "url": "https://surfdrive.surf.nl/files/index.php/s/fI0Gmuu5O1MJAI9", "type": [ "Terms of use" ], "note": "Exposome-NL data platform Data Access and Publication Policy" } ], "publication": [ { "doi": "10.1126/science.aay3164", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "The exposome and health: Where chemistry meets biology", "abstract": "Despite extensive evidence showing that exposure to specific chemicals can lead to disease, current research approaches and regulatory policies fail to address the chemical complexity of our world. To safeguard current and future generations from the increasing number of chemicals polluting our environment, a systematic and agnostic approach is needed. The “exposome” concept strives to capture the diversity and range of exposures to synthetic chemicals, dietary constituents, psychosocial stressors, and physical factors, as well as their corresponding biological responses. Technological advances such as high-resolution mass spectrometry and network science have allowed us to take the first steps toward a comprehensive assessment of the exposome. Given the increased recognition of the dominant role that nongenetic factors play in disease, an effort to characterize the exposome at a scale comparable to that of the human genome is warranted.", "date": "2020-01-24T00:00:00Z", "citationCount": 597, "authors": [ { "name": "Vermeulen R." }, { "name": "Schymanski E.L." }, { "name": "Barabasi A.-L." }, { "name": "Miller G.W." } ], "journal": "Science" } }, { "doi": "10.1097/EE9.0000000000000162", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Developing the building blocks to elucidate the impact of the urban exposome on cardiometabolic-pulmonary disease: The EU EXPANSE project", "abstract": "By 2030, more than 80% of Europe's population will live in an urban environment. The urban exposome, consisting of factors such as where we live and work, where and what we eat, our social network, and what chemical and physical hazards we are exposed to, provides important targets to improve population health. The EXPANSE (EXposome Powered tools for healthy living in urbAN SEttings) project will study the impact of the urban exposome on the major contributors to Europe's burden of disease: Cardio-Metabolic and Pulmonary Disease. EXPANSE will address one of the most pertinent questions for urban planners, policy makers, and European citizens: \"How to maximize one's health in a modern urban environment?\" EXPANSE will take the next step in exposome research by (1) bringing together exposome and health data of more than 55 million adult Europeans and OMICS information for more than 2 million Europeans; (2) perform personalized exposome assessment for 5,000 individuals in five urban regions; (3) applying ultra-high-resolution mass-spectrometry to screen for chemicals in 10,000 blood samples; (4) evaluating the evolution of the exposome and health through the life course; and (5) evaluating the impact of changes in the urban exposome on the burden of cardiometabolic and pulmonary disease. EXPANSE will translate its insights and innovations into research and dissemination tools that will be openly accessible via the EXPANSE toolbox. By applying innovative ethics-by-design throughout the project, the social and ethical acceptability of these tools will be safeguarded. EXPANSE is part of the European Human Exposome Network.", "date": "2021-08-01T00:00:00Z", "citationCount": 38, "authors": [ { "name": "Vlaanderen J." }, { "name": "De Hoogh K." }, { "name": "Hoek G." }, { "name": "Peters A." }, { "name": "Probst-Hensch N." }, { "name": "Scalbert A." }, { "name": "Melen E." }, { "name": "Tonne C." }, { "name": "De Wit G.A." }, { "name": "Chadeau-Hyam M." }, { "name": "Katsouyanni K." }, { "name": "Esko T." }, { "name": "Jongsma K.R." }, { "name": "Vermeulen R." } ], "journal": "Environmental Epidemiology" } } ], "credit": [ { "name": "Roel Vermeulen", "email": "R.C.H.Vermeulen@uu.nl", "url": null, "orcidid": "https://orcid.org/0000-0003-4082-8163", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact" ], "note": null }, { "name": "Zimbo Boudewijns", "email": "z.s.r.m.boudewijns@uu.nl", "url": null, "orcidid": "https://orcid.org/0000-0002-9383-9571", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Maintainer" ], "note": null }, { "name": "Lloyd Roga", "email": "l.q.roga@uu.nl", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null } ], "owner": "Channel2291", "additionDate": "2025-03-17T14:01:59.601345Z", "lastUpdate": "2025-04-15T08:35:02.159681Z", "editPermission": { "type": "group", "authors": [ "hkucukali" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "hictkpy", "description": "Python bindings for hictk: read and write .cool and .hic files directly from Python", "homepage": "https://github.com/paulsengroup/hictkpy", "biotoolsID": "hictkpy", "biotoolsCURIE": "biotools:hictkpy", "version": [ "0.0.1", "0.0.2", "0.0.3", "0.0.4", "0.0.5", "1.0.0", "1.1.0", "1.2.0" ], "otherID": [], "relation": [ { "biotoolsID": "hictk", "type": "uses" } ], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/paulsengroup/hictkpy", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/paulsengroup/hictkpy/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/paulsengroup/hictkpy/discussions", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://github.com/paulsengroup/hictkpy/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://pypi.org/project/hictkpy/", "type": "Binaries", "note": null, "version": null }, { "url": "https://anaconda.org/bioconda/hictkpy", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://hictkpy.readthedocs.io/en/stable/", "type": [ "General" ], "note": null }, { "url": "https://hictkpy.readthedocs.io/en/stable/installation.html", "type": [ "Installation instructions" ], "note": null }, { "url": "https://hictkpy.readthedocs.io/en/stable/quickstart.html", "type": [ "Quick start guide" ], "note": null }, { "url": "https://hictkpy.readthedocs.io/en/stable/api/index.html", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btae408", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "hictk: blazing fast toolkit to work with. hic and. cool files", "abstract": "Motivation: Hi-C is gaining prominence as a method for mapping genome organization. With declining sequencing costs and a growing demand for higher-resolution data, efficient tools for processing Hi-C datasets at different resolutions are crucial. Over the past decade, the. hic and Cooler file formats have become the de-facto standard to store interaction matrices produced by Hi-C experiments in binary format. Interoperability issues make it unnecessarily difficult to convert between the two formats and to develop applications that can process each format natively. Results: We developed hictk, a toolkit that can transparently operate on. hic and. cool files with excellent performance. The toolkit is written in C++ and consists of a C++ library with Python and R bindings as well as CLI tools to perform common operations directly from the shell, including converting between. hic and. mcool formats. We benchmark the performance of hictk and compare it with other popular tools and libraries. We conclude that hictk significantly outperforms existing tools while providing the flexibility of natively working with both file formats without code duplication.", "date": "2024-07-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Rossini R." }, { "name": "Paulsen J." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "robomics", "additionDate": "2024-04-18T08:31:46.459964Z", "lastUpdate": "2025-04-14T22:54:26.266145Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "hictk", "description": "Blazing fast toolkit to work with .hic and .cool files", "homepage": "https://github.com/paulsengroup/hictk", "biotoolsID": "hictk", "biotoolsCURIE": "biotools:hictk", "version": [ "0.0.1", "0.0.2", "0.0.3", "0.0.4", "0.0.5", "0.0.6", "0.0.7", "0.0.8", "0.0.9", "0.0.10", "0.0.11", "0.0.12", "1.0.0", "2.0.0", "2.0.1", "2.0.2", "2.1.0", "2.1.1" ], "otherID": [], "relation": [ { "biotoolsID": "hictkpy", "type": "usedBy" }, { "biotoolsID": "hictkr", "type": "usedBy" } ], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/paulsengroup/hictk", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/paulsengroup/hictk/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/paulsengroup/hictk/discussions", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://github.com/paulsengroup/hictk/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://anaconda.org/bioconda/hictk", "type": "Binaries", "note": null, "version": null }, { "url": "https://github.com/paulsengroup/hictk/pkgs/container/hictk", "type": "Container file", "note": null, "version": null } ], "documentation": [ { "url": "https://hictk.readthedocs.io/en/stable/index.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btae408", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "hictk: blazing fast toolkit to work with. hic and. cool files", "abstract": "Motivation: Hi-C is gaining prominence as a method for mapping genome organization. With declining sequencing costs and a growing demand for higher-resolution data, efficient tools for processing Hi-C datasets at different resolutions are crucial. Over the past decade, the. hic and Cooler file formats have become the de-facto standard to store interaction matrices produced by Hi-C experiments in binary format. Interoperability issues make it unnecessarily difficult to convert between the two formats and to develop applications that can process each format natively. Results: We developed hictk, a toolkit that can transparently operate on. hic and. cool files with excellent performance. The toolkit is written in C++ and consists of a C++ library with Python and R bindings as well as CLI tools to perform common operations directly from the shell, including converting between. hic and. mcool formats. We benchmark the performance of hictk and compare it with other popular tools and libraries. We conclude that hictk significantly outperforms existing tools while providing the flexibility of natively working with both file formats without code duplication.", "date": "2024-07-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Rossini R." }, { "name": "Paulsen J." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "robomics", "additionDate": "2024-02-02T14:42:46.030561Z", "lastUpdate": "2025-04-14T22:54:16.319235Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "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": "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": "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": "CheckM2", "description": "Rapid assessment of genome bin quality using machine learning.\n\nCheckM2 uses two distinct machine learning models to predict genome completeness. The 'general' gradient boost model is able to generalize well and is intended to be used on organisms not well represented in GenBank or RefSeq (roughly, when an organism is novel at the level of order, class or phylum). The 'specific' neural network model is more accurate when predicting completeness of organisms more closely related to the reference training set (roughly, when an organism belongs to a known species, genus or family). CheckM2 uses a cosine similarity calculation to automatically determine the appropriate completeness model for each input genome, but you can also force the use of a particular completeness model, or get the prediction outputs for both. There is only one contamination model (based on gradient boost) which is applied regardless of taxonomic novelty and works well across all cases.", "homepage": "https://github.com/chklovski/CheckM2", "biotoolsID": "checkm2", "biotoolsCURIE": "biotools:checkm2", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_0194", "term": "Phylogenomics" }, { "uri": "http://edamontology.org/topic_3572", "term": "Data quality management" } ], "operatingSystem": [ "Linux" ], "language": [], "license": "GPL-3.0", "collectionID": [ "NFDI4Microbiota" ], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.nature.com/articles/s41592-023-01940-w", "type": [ "Other" ], "note": null } ], "download": [ { "url": "https://doi.org/10.5281/zenodo.14897628", "type": "Biological data", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/chklovski/CheckM2", "type": [ "Quick start guide" ], "note": null } ], "publication": [ { "doi": "10.1038/s41592-023-01940-w", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "Kasmanas", "additionDate": "2025-04-08T11:23:25.060891Z", "lastUpdate": "2025-04-08T11:23:25.063938Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "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": "LncRNAway", "description": "A web-based sgRNA design tool for precise and effective suppression of long noncoding RNAs", "homepage": "https://www.lncrnaway.com", "biotoolsID": "lncrnaway", "biotoolsCURIE": "biotools:lncrnaway", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0230", "term": "Sequence generation" }, { "uri": "http://edamontology.org/operation_0308", "term": "PCR primer design" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1033", "term": "Ensembl gene ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1026", "term": "Gene symbol" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3495", "term": "RNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_2305", "term": "GFF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3495", "term": "RNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_0972", "term": "Text mining report" }, "format": [] } ], "note": "Design of sgRNA for lncRNA knockout; Primer design for PCR and qPCR to knockout detection.", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0085", "term": "Functional genomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.lncrnaway.com", "type": [ "Service" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkae383", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "LncRNAway: A web-based sgRNA design tool for precise and effective suppression of long noncoding RNAs", "abstract": "Thousands of long noncoding RNAs (lncRNAs) have been annotated via high-throughput RNA sequencing, yet only a small fraction have been functionally investigated. Genomic knockout is the mainstream strategy for studying the biological function of protein-coding genes and lncRNAs, whereas the complexity of the lncRNA locus, especially the natural antisense lncRNAs (NAT-lncRNAs), presents great challenges. Knocking out lncRNAs often results in unintended disruptions of neighboring protein-coding genes and small RNAs, leading to ambiguity in observing phenotypes and interpreting biological function. To address this issue, we launched LncRNAway, a user-friendly web tool based on the BESST (branchpoint to 3' splicing site targeting) method, to design sgRNAs for lncRNA knockout. LncRNAway not only provides specific and effective lncRNA knockout guidelines but also integrates genotyping primers and quantitative PCR primers designing, thereby streamlining experimental procedures of lncRNA function study. LncRNAway is freely available at https://www.lncrnaway.com.", "date": "2024-07-05T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Zhang S." }, { "name": "Wang S." }, { "name": "Lu F." }, { "name": "Bie L." }, { "name": "Luo Y." }, { "name": "Sun J." }, { "name": "Zhang Y." }, { "name": "Wang Y." }, { "name": "Zhang Y." }, { "name": "Lyu Q.R." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Chongqing General Hospital, Chongqing University, Lyu Lab", "email": "qlyu@cqu.edu.cn", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "inespinheiro", "additionDate": "2025-03-28T11:01:27.681477Z", "lastUpdate": "2025-03-28T11:54:36.402981Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "IsoVis", "description": "A webserver for visualization and annotation of alternative RNA isoforms", "homepage": "https://isomix.org/isovis/", "biotoolsID": "isovis", "biotoolsCURIE": "biotools:isovis", "version": [ "v1.10" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2877", "term": "Protein complex" }, "format": [ { "uri": "http://edamontology.org/format_2305", "term": "GFF" }, { "uri": "http://edamontology.org/format_2306", "term": "GTF" }, { "uri": "http://edamontology.org/format_3003", "term": "BED" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0883", "term": "Structure" }, "format": [] } ], "note": "isoform stack", "cmd": "--" } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_4019", "term": "Biosciences" } ], "operatingSystem": [ "Linux", "Windows" ], "language": [ "JavaScript" ], "license": "MPL-2.0", "collectionID": [ "IsoVis" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "UK" ], "elixirCommunity": [], "link": [ { "url": "https://isomix.org/isovis/", "type": [ "Other" ], "note": "a webserver" }, { "url": "https://github.com/ClarkLaboratory/IsoVis?tab=MPL-2.0-1-ov-file", "type": [ "Repository" ], "note": null }, { "url": "https://academic.oup.com/nar/article/52/W1/W341/7665639", "type": [ "Other" ], "note": "Nucleic Acids Research" } ], "download": [ { "url": "https://github.com/ClarkLaboratory/IsoVis.git", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://isovis.gandallab.org/tutorial/", "type": [ "User manual" ], "note": null } ], "publication": [], "credit": [], "owner": "Kvetoslava_Mahutova", "additionDate": "2025-03-28T11:20:32.972026Z", "lastUpdate": "2025-03-28T11:41:10.718643Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "LifeMonitor", "description": "LifeMonitor is a service to support the sustainability and reusability of published computational workflows. It provides:\n* periodic testing;\n* test monitoring and notification;\n* automated checks and templates for workflow best practices.", "homepage": "https://lifemonitor.eu", "biotoolsID": "lifemonitor", "biotoolsCURIE": "biotools:lifemonitor", "version": [], "otherID": [], "relation": [ { "biotoolsID": "rocrate-validator", "type": "uses" } ], "function": [], "toolType": [ "Web application", "Web API", "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_3372", "term": "Software engineering" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" }, { "uri": "http://edamontology.org/topic_4010", "term": "Open science" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python", "JavaScript" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/crs4/life_monitor", "type": [ "Repository" ], "note": null }, { "url": "https://api.lifemonitor.eu", "type": [ "Service" ], "note": "REST API (production instance)" }, { "url": "https://api.dev/lifemonitor.eu", "type": [ "Service" ], "note": "REST API (dev instance)" }, { "url": "https://app.lifemonitor.eu", "type": [ "Service" ], "note": "Web App (production instance)" }, { "url": "https://app.dev.lifemonitor.eu", "type": [ "Service" ], "note": "Web App (dev instance)" }, { "url": "https://github.com/crs4/life_monitor/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/apps/lifemonitor", "type": [ "Service" ], "note": "GitHub App" } ], "download": [], "documentation": [ { "url": "https://lifemonitor.eu", "type": [ "User manual" ], "note": null }, { "url": "https://api.lifemonitor.eu/openapi.html", "type": [ "API documentation" ], "note": null } ], "publication": [], "credit": [ { "name": "Marco Enrico Piras", "email": "marcoenrico.piras@crs4.it", "url": null, "orcidid": "https://orcid.org/0000-0002-5207-0030", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "Simone Leo", "email": "simone.leo@crs4.it", "url": null, "orcidid": "https://orcid.org/0000-0001-8271-5429", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Developer" ], "note": null }, { "name": "Luca Pireddu", "email": "luca.pireddu@crs4.it", "url": null, "orcidid": "https://orcid.org/0000-0002-4663-5613", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor", "Developer" ], "note": null }, { "name": "CRS4", "email": null, "url": "https://www.crs4.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null }, { "name": "EOSC-Life", "email": null, "url": "https://www.eosc-life.eu/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [], "note": null } ], "owner": "mep", "additionDate": "2025-03-25T12:17:42.278603Z", "lastUpdate": "2025-03-25T12:17:42.289116Z", "editPermission": { "type": "group", "authors": [ "mep", "ilveroluca" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "INPS-MD", "description": "Predicting the impact of mutations on protein stability from sequence and structure.", "homepage": "http://inpsmd.biocomp.unibo.it", "biotoolsID": "inps-md", "biotoolsCURIE": "biotools:inps-md", "version": [ "2.0" ], "otherID": [], "relation": [], "function": [ { "operation": [], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "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": "Prediction of the impact of non-synonymous polymorphisms on protein stability from sequence.", "cmd": null }, { "operation": [], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1008", "term": "Polypeptide chain ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [] } ], "note": "Prediction of the impact of non-synonymous polymorphisms on protein stability from structure.", "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": [ "3D-BioInfo" ], "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": "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": "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. The script is designed to handle large raster datasets efficiently by dividing the workload across multiple CPU cores.", "homepage": "https://github.com/UtrechtUniversity/raster_extraction", "biotoolsID": "raster_extraction", "biotoolsCURIE": "biotools:raster_extraction", "version": [], "otherID": [], "relation": [ { "biotoolsID": "exposome_maps", "type": "uses" } ], "function": [ { "operation": [], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3855", "term": "Environmental sciences" }, { "uri": "http://edamontology.org/topic_3071", "term": "Data management" } ], "operatingSystem": [], "language": [], "license": "Not licensed", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [ { "name": "Lloyd Roga", "email": "l.q.roga@uu.nl", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer", "Maintainer" ], "note": null } ], "owner": "Channel2291", "additionDate": "2025-03-17T14:11:03.252329Z", "lastUpdate": "2025-03-17T14:13:20.238876Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Health Data Nexus", "description": "The Health Data Nexus is T-CAIREM's unique online platform for health data sharing & analytics that emphasizes patient privacy and security, provides transparent and speedy access, and simplifies data discovery and analysis.", "homepage": "https://healthdatanexus.ai/", "biotoolsID": "hdn", "biotoolsCURIE": "biotools:hdn", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3071", "term": "Data management" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" } ], "operatingSystem": [], "language": [], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://tcairem.utoronto.ca/infrastructure-overview", "type": [ "Other" ], "note": null }, { "url": "https://github.com/T-CAIREM/physionet-build", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "rutvikrj26", "additionDate": "2025-03-16T20:15:23.278615Z", "lastUpdate": "2025-03-16T20:26:12.603608Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "GTestimate", "description": "GTestimate is a scRNA-seq normalization method. In contrast to other methods it uses the Simple Good-Turing estimator for the per cell relative gene expression estimation.", "homepage": "https://github.com/Martin-Fahrenberger/GTestimate", "biotoolsID": "gtestimate", "biotoolsCURIE": "biotools:gtestimate", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3435", "term": "Standardisation and normalisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3917", "term": "Count matrix" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3112", "term": "Gene expression matrix" }, "format": [] } ], "note": "GTestimate is provided as an R-package containing the GTestimate() function.", "cmd": "GTestimate()" } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Martin-Fahrenberger/GTestimate", "type": [ "Issue tracker", "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://github.com/Martin-Fahrenberger/GTestimate", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1101/2024.07.02.601501", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": "2", "note": "preprint version 2", "metadata": null } ], "credit": [], "owner": "martin_fahrenberger", "additionDate": "2025-03-12T15:38:32.218141Z", "lastUpdate": "2025-03-12T15:38:32.221353Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Arabidopsis Co-expression Tool (ACT)", "description": "The Arabidopsis Coexpression Tool (ACT) is based on the coexpression analysis of 21273 Arabidopsis thaliana genes from gene pair correlation data of 3500 Affymetrix Arabidopsis ATH1 Genome Array Chip microarray samples.", "homepage": "https://www.michalopoulos.net/act/", "biotoolsID": "act", "biotoolsCURIE": "biotools:act", "version": [ "2.6" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2938", "term": "Dendrogram visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1025", "term": "Gene identifier" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3271", "term": "Gene tree" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Greece" ], "elixirCommunity": [ "Plant Sciences" ], "link": [], "download": [], "documentation": [ { "url": "https://www.michalopoulos.net/act2.6/help.php", "type": [ "FAQ" ], "note": null } ], "publication": [ { "doi": "10.3390/genes16030258", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null }, { "doi": "10.1016/j.xpro.2022.101208", "pmid": "35243384", "pmcid": "PMC8885756", "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "Gene coexpression analysis in Arabidopsis thaliana based on public microarray data", "abstract": "Coexpressed genes tend to participate in related biological processes. 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. 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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. 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Bergmann", "email": "frank.bergmann@bioquant.uni-heidelberg.de", "url": null, "orcidid": "https://orcid.org/0000-0001-5553-4702", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer" ], "note": null } ], "owner": "frankbergmann", "additionDate": "2025-02-26T14:07:27.855714Z", "lastUpdate": "2025-02-26T14:09:14.108566Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "COPASI", "description": "Open-source software application for creating and solving mathematical models of biological processes such as metabolic networks, cell-signaling pathways, regulatory networks, infectious diseases, and many others. 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Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods. Results: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic-stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation. © 2006 Oxford University Press.", "date": "2006-12-15T00:00:00Z", "citationCount": 1960, "authors": [ { "name": "Hoops S." }, { "name": "Gauges R." }, { "name": "Lee C." }, { "name": "Pahle J." }, { "name": "Simus N." }, { "name": "Singhal M." }, { "name": "Xu L." }, { "name": "Mendes P." }, { "name": "Kummer U." } ], "journal": "Bioinformatics" } }, { "doi": "10.1007/978-1-59745-525-1_2", "pmid": "19399433", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Computational modeling of biochemical networks using COPASI", "abstract": "Computational modeling and simulation of biochemical networks is at the core of systems biology and this includes many types of analyses that can aid understanding of how these systems work. COPASI is a generic software package for modeling and simulation of biochemical networks which provides many of these analyses in convenient ways that do not require the user to program or to have deep knowledge of the numerical algorithms. Here we provide a description of how these modeling techniques can be applied to biochemical models using COPASI. The focus is both on practical aspects of software usage as well as on the utility of these analyses in aiding biological understanding. Practical examples are described for steady-state and time-course simulations, stoichiometric analyses, parameter scanning, sensitivity analysis (including metabolic control analysis), global optimization, parameter estimation, and stochastic simulation. The examples used are all published models that are available in the BioModels database in SBML format. © 2009 Humana Press.", "date": "2009-12-01T00:00:00Z", "citationCount": 168, "authors": [ { "name": "Mendes P." }, { "name": "Hoops S." }, { "name": "Sahle S." }, { "name": "Gauges R." }, { "name": "Dada J." }, { "name": "Kummer U." } ], "journal": "Methods in Molecular Biology" } }, { "doi": "10.1016/j.jbiotec.2017.06.1200", "pmid": "28655634", "pmcid": "PMC5623632", "type": [], "version": null, "note": null, "metadata": { "title": "COPASI and its applications in biotechnology", "abstract": "COPASI is software used for the creation, modification, simulation and computational analysis of kinetic models in various fields. It is open-source, available for all major platforms and provides a user-friendly graphical user interface, but is also controllable via the command line and scripting languages. These are likely reasons for its wide acceptance. We begin this review with a short introduction describing the general approaches and techniques used in computational modeling in the biosciences. Next we introduce the COPASI package, and its capabilities, before looking at typical applications of COPASI in biotechnology.", "date": "2017-11-10T00:00:00Z", "citationCount": 75, "authors": [ { "name": "Bergmann F.T." }, { "name": "Hoops S." }, { "name": "Klahn B." }, { "name": "Kummer U." }, { "name": "Mendes P." }, { "name": "Pahle J." }, { "name": "Sahle S." } ], "journal": "Journal of Biotechnology" } } ], "credit": [ { "name": null, "email": null, "url": "http://copasi.org/About/Team/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Frank T. 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Several biological databases exist that provide such information. However, in many cases these databases provide partly different and inconsistent genome annotations.Description: We analysed nine prokaryotic genomes and found about 70% inconsistencies in the enzyme predictions of the main annotation resources. Therefore, we implemented the annotation pipeline EnzymeDetector. This tool automatically compares and evaluates the assigned enzyme functions from the main annotation databases and supplements them with its own function prediction. This is based on a sequence similarity analysis, on manually created organism-specific enzyme information from BRENDA (Braunschweig Enzyme Database), and on sequence pattern searches.Conclusions: EnzymeDetector provides a fast and comprehensive overview of the available enzyme function annotations for a genome of interest. The web interface allows the user to work with customisable weighting schemes and cut-offs for the different prediction methods. These customised quality criteria can easily be applied, and the resulting annotation can be downloaded. The summarised view of all used annotation sources provides up-to-date information. Annotation errors that occur in only one of the databases can be recognised (because of their low relevance score). The results are stored in a database and can be accessed at http://enzymedetector.tu-bs.de. © 2011 Quester and Schomburg; licensee BioMed Central Ltd.", "date": "2011-09-23T00:00:00Z", "citationCount": 49, "authors": [ { "name": "Quester S." }, { "name": "Schomburg D." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1093/nar/gkaa1025", "pmid": "33211880", "pmcid": "PMC7779020", "type": [ "Review" ], "version": null, "note": null, "metadata": { "title": "BRENDA, the ELIXIR core data resource in 2021: New developments and updates", "abstract": "The BRENDA enzyme database (https://www.brendaenzymes.org), established in 1987, has evolved into the main collection of functional enzyme and metabolism data. In 2018, BRENDA was selected as an ELIXIR Core Data Resource. BRENDA provides reliable data, continuous curation and updates of classified enzymes, and the integration of newly discovered enzymes. The main part contains >5 million data for ∼90 000 enzymes from ∼13 000 organisms, manually extracted from ∼157 000 primary literature references, combined with information of text and data mining, data integration, and prediction algorithms. Supplements comprise disease-related data, protein sequences, 3D structures, genome annotations, lig- and information, taxonomic, bibliographic, and kinetic data. BRENDA offers an easy access to enzyme information from quick to advanced searches, text- and structured-based queries for enzyme-ligand interactions, word maps, and visualization of enzyme data. The BRENDA Pathway Maps are completely revised and updated for an enhanced interactive and intuitive usability. The new design of the Enzyme Summary Page provides an improved access to each individual enzyme. A new protein structure 3D viewer was integrated. The prediction of the intracellular localization of eukaryotic enzymes has been implemented. 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Superposition of RNA 3D structures is the most accurate method for comparative analysis of RNA molecules and for inferring structure-based sequence alignments. Topology-independent superposition is particularly relevant, as evidenced by structurally similar RNAs with sequence permutations such as tRNA and Y RNA. To date, state-of-the-art methods for RNA 3D structure superposition rely on intricate heuristics, and the potential for topology-independent superposition has not been exhausted. Recently, we introduced the ARTEM method for unrestrained pairwise superposition of RNA 3D modules and now we developed it further to solve the global RNA 3D structure alignment problem. Our new tool ARTEMIS significantly outperforms state-of-the-art tools in both sequentially-ordered and topology-independent RNA 3D structure superposition. Using ARTEMIS we discovered a helical packing motif to be preserved within different backbone topology contexts across various non-coding RNAs, including multiple ribozymes and riboswitches. We anticipate that ARTEMIS will be essential for elucidating the landscape of RNA 3D folds and motifs featuring sequence permutations that thus far remained unexplored due to limitations in previous computational approaches.", "date": "2024-10-14T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Bohdan D.R." }, { "name": "Bujnicki J.M." }, { "name": "Baulin E.F." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1101/2024.04.06.588371", "pmid": null, "pmcid": null, "type": [], "version": "version 1.0", "note": null, "metadata": null } ], "credit": [ { "name": "Davyd Bohdan", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-6456-6658", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Janusz Bujnicki", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-6633-165X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Eugene Baulin", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-4694-9783", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "febos", "additionDate": "2024-09-09T07:49:35.385723Z", "lastUpdate": "2025-01-30T09:07:50.841042Z", "editPermission": { "type": "private", "authors": [ "febos" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PhageDive", "description": "PhageDive is a specific database for bacteriophages and archaeal viruses. Built on the BacDive model, it gathers and links all the experimental data and metadata of the viruses present in different culture collections. Its implementation aims to facilitate access to all viruses information for the scientific community. The database covers taxonomy, host strain, phage morphology, life cycle, origin and genomic data.", "homepage": "https://phagedive.dsmz.de/", "biotoolsID": "phagedive", "biotoolsCURIE": "biotools:phagedive", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" }, { "uri": "http://edamontology.org/topic_0781", "term": "Virology" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": "CC-BY-4.0", "collectionID": [ "DSMZ Digital Diversity" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data" ], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkae878", "pmid": "39373542", "pmcid": "PMC11701545", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "PhageDive: the comprehensive strain database of prokaryotic viral diversity", "abstract": "Prokaryotic viruses represent the most diverse and abundant biological entities on Earth. So far, data on bacteriophages are not standardized, not readily available for comparative analyses and cannot be linked to the rapidly growing (meta)genomic data. We developed PhageDive (https://phagedive.dsmz.de), a comprehensive database for prokaryotic viruses gathering all existing data dispersed across multiple sources, like scientific publications, specialized databases or internal files of culture collections. PhageDive allows to link own research data to the existing information through an easy and central access, providing fields for various experimental data (host range, genomic data, etc.) and available metadata (e.g. geographical origin, isolation source). An important feature is the link between experimental data, the culture collection number and the repository of the corresponding physical bioresource. To date, PhageDive covers 1167 phages from three different world-renowned public collections (DSMZ, Félix d’Hérelle Reference Center for Bacterial Viruses and NCTC) and features an advanced search function using all data fields from the sections like taxonomy or morphology by controlled vocabulary and ontologies. PhageDive is fully interoperable with other resources including NCBI, the Viral Host Range database (VHRdb) of Institute Pasteur or the BacDive and MediaDive databases of DSMZ.", "date": "2025-01-06T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Rolland C." }, { "name": "Wittmann J." }, { "name": "Reimer L.C." }, { "name": "Carbasse J.S." }, { "name": "Schober I." }, { "name": "Dudek C.-A." }, { "name": "Ebeling C." }, { "name": "Koblitz J." }, { "name": "Bunk B." }, { "name": "Overmann J." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH", "email": null, "url": "https://www.dsmz.de/", "orcidid": null, "gridid": null, "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Maintainer" ], "note": null } ], "owner": "isabelschober", "additionDate": "2025-01-29T09:17:22.793965Z", "lastUpdate": "2025-01-29T09:24:11.296689Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BRENDA", "description": "Internationally leading information system on all aspects of enzymes, including function, structure, involvement in diseases, application, engineering, and molecular properties. The database includes hundreds of milllions of enzyme data and is compiled from manual literature annotation, data integration from other databases and predicted enzyme functions and locations.", "homepage": "http://www.brenda-enzymes.org", "biotoolsID": "brenda", "biotoolsCURIE": "biotools:brenda", "version": [], "otherID": [], "relation": [ { "biotoolsID": "bto", "type": "includes" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_0346", "term": "Sequence similarity search" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_0306", "term": "Text mining" }, { "uri": "http://edamontology.org/operation_3194", "term": "Genome feature comparison" }, { "uri": "http://edamontology.org/operation_0570", "term": "Structure visualisation" }, { "uri": "http://edamontology.org/operation_3208", "term": "Genome visualisation" }, { "uri": "http://edamontology.org/operation_0305", "term": "Literature search" }, { "uri": "http://edamontology.org/operation_0338", "term": "Sequence database search" }, { "uri": "http://edamontology.org/operation_3083", "term": "Pathway or network visualisation" }, { "uri": "http://edamontology.org/operation_0360", "term": "Structural similarity search" }, { "uri": "http://edamontology.org/operation_0269", "term": "Transmembrane protein prediction" }, { "uri": "http://edamontology.org/operation_2241", "term": "Transmembrane protein visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2909", "term": "Organism name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0990", "term": "Compound name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2299", "term": "Gene name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1127", "term": "PDB ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2291", "term": "UniProt ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3021", "term": "UniProt accession" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2108", "term": "Reaction ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2342", "term": "Pathway or network name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2365", "term": "Pathway or network accession" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1187", "term": "PubMed ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1046", "term": "Strain name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1179", "term": "NCBI taxonomy ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1051", "term": "Ontology name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1012", "term": "Enzyme name" }, "format": [] }, { "data": 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"format": [] }, { "data": { "uri": "http://edamontology.org/data_1179", "term": "NCBI taxonomy ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1039", "term": "SCOP domain identifier" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2700", "term": "CATH identifier" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1012", "term": "Enzyme name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1011", "term": "EC number" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2024", "term": "Enzyme kinetics data" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3292", "term": "Biochemistry" }, { "uri": "http://edamontology.org/topic_0821", "term": "Enzymes" }, { "uri": "http://edamontology.org/topic_3070", "term": "Biology" }, { "uri": "http://edamontology.org/topic_3297", "term": "Biotechnology" }, { "uri": "http://edamontology.org/topic_3473", "term": "Data mining" }, { "uri": "http://edamontology.org/topic_3344", "term": "Biomedical science" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "CC-BY-4.0", "collectionID": [ "de.NBI", "DSMZ Digital Diversity" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access", "elixirPlatform": [ "Data", "Tools", "Interoperability" ], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://www.dsmz.de/", "type": [ "Other" ], "note": null }, { "url": "https://hub.dsmz.de/#/", "type": [ "Service" ], "note": null }, { "url": "https://www.brenda-enzymes.org/", "type": [ "Service" ], "note": null }, { "url": "https://brenda-enzymes.org/support.php", "type": [ "Helpdesk" ], "note": null } ], "download": [], "documentation": [ { "url": "http://www.brenda-enzymes.org/copy.php", "type": [ "Terms of use" ], "note": null }, { "url": "http://www.brenda-enzymes.org/introduction.php", "type": [ "Citation instructions" ], "note": null }, { "url": "https://www.brenda-enzymes.org/tutorial.php", "type": [ "Training material" ], "note": null }, { "url": "https://www.brenda-enzymes.org/help.php", "type": [ "Training material" ], "note": null }, { "url": "https://www.brenda-enzymes.org/faq.php", "type": [ "FAQ" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkaa1025", "pmid": "33211880", "pmcid": "PMC7779020", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "BRENDA, the ELIXIR core data resource in 2021: New developments and updates", "abstract": "The BRENDA enzyme database (https://www.brendaenzymes.org), established in 1987, has evolved into the main collection of functional enzyme and metabolism data. In 2018, BRENDA was selected as an ELIXIR Core Data Resource. BRENDA provides reliable data, continuous curation and updates of classified enzymes, and the integration of newly discovered enzymes. The main part contains >5 million data for ∼90 000 enzymes from ∼13 000 organisms, manually extracted from ∼157 000 primary literature references, combined with information of text and data mining, data integration, and prediction algorithms. Supplements comprise disease-related data, protein sequences, 3D structures, genome annotations, lig- and information, taxonomic, bibliographic, and kinetic data. BRENDA offers an easy access to enzyme information from quick to advanced searches, text- and structured-based queries for enzyme-ligand interactions, word maps, and visualization of enzyme data. The BRENDA Pathway Maps are completely revised and updated for an enhanced interactive and intuitive usability. The new design of the Enzyme Summary Page provides an improved access to each individual enzyme. A new protein structure 3D viewer was integrated. The prediction of the intracellular localization of eukaryotic enzymes has been implemented. The new EnzymeDetector combines BRENDA enzyme annotations with protein and genome databases for the detection of eukaryotic and prokaryotic enzymes.", "date": "2021-01-08T00:00:00Z", "citationCount": 393, "authors": [ { "name": "Chang A." }, { "name": "Jeske L." }, { "name": "Ulbrich S." }, { "name": "Hofmann J." }, { "name": "Koblitz J." }, { "name": "Schomburg I." }, { "name": "Neumann-Schaal M." }, { "name": "Jahn D." }, { "name": "Schomburg D." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gky1048", "pmid": "30395242", "pmcid": "PMC6323942", "type": [], "version": null, "note": null, "metadata": { "title": "BRENDA in 2019: A European ELIXIR core data resource", "abstract": "The BRENDA enzyme database (www.brenda-enzymes.org), recently appointed ELIXIR Core Data Resource, is the main enzyme and enzyme-ligand information system. The core database provides a comprehensive overview on enzymes. A collection of 4.3 million data for ∼84 000 enzymes manually evaluated and extracted from ∼140 000 primary literature references is combined with information obtained by text and data mining, data integration and prediction algorithms. Supplements comprise disease-related data, protein sequences, 3D structures, predicted enzyme locations and genome annotations. Major developments are a revised ligand summary page and the structure search now including a similarity and isomer search. BKMS-react, an integrated database containing known enzyme-catalyzed reactions, is supplemented with further reactions and improved access to pathway connections. In addition to existing enzyme word maps with graphical information of enzyme specific terms, plant word maps have been developed. They show a graphical overview of terms, e.g. enzyme or plant pathogen information, connected to specific plants. An organism summary page showing all relevant information, e.g. taxonomy and synonyms linked to enzyme data, was implemented. Based on a decision by the IUBMB enzyme task force the enzyme class EC 7 has been established for 'translocases-, enzymes that catalyze a transport of ions or metabolites across cellular membranes.", "date": "2019-01-08T00:00:00Z", "citationCount": 296, "authors": [ { "name": "Jeske L." }, { "name": "Placzek S." }, { "name": "Schomburg I." }, { "name": "Chang A." }, { "name": "Schomburg D." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1016/j.jbiotec.2017.04.020", "pmid": "28438579", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "The BRENDA enzyme information system–From a database to an expert system", "abstract": "Enzymes, representing the largest and by far most complex group of proteins, play an essential role in all processes of life, including metabolism, gene expression, cell division, the immune system, and others. Their function, also connected to most diseases or stress control makes them interesting targets for research and applications in biotechnology, medical treatments, or diagnosis. Their functional parameters and other properties are collected, integrated, and made available to the scientific community in the BRaunschweig ENzyme DAtabase (BRENDA). In the last 30 years BRENDA has developed into one of the most highly used biological databases worldwide. The data contents, the process of data acquisition, data integration and control, the ways to access the data, and visualizations provided by the website are described and discussed.", "date": "2017-11-10T00:00:00Z", "citationCount": 133, "authors": [ { "name": "Schomburg I." }, { "name": "Jeske L." }, { "name": "Ulbrich M." }, { "name": "Placzek S." }, { "name": "Chang A." }, { "name": "Schomburg D." } ], "journal": "Journal of Biotechnology" } }, { "doi": "10.1093/nar/gku1068", "pmid": "25378310", "pmcid": "PMC4383907", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BRENDA in 2015: Exciting developments in its 25th year of existence", "abstract": "The BRENDA enzyme information system (http://www.brenda-enzymes.org/) has developed into an elaborate system of enzyme and enzyme-ligand information obtained from different sources, combined with flexible query systems and evaluation tools. The information is obtained by manual extraction from primary literature, text and data mining, data integration, and prediction algorithms. Approximately 300 million data include enzyme function and molecular data from more than 30 000 organisms. The manually derived core contains 3 million data from 77 000 enzymes annotated from 135 000 literature references. Each entry is connected to the literature reference and the source organism. They are complemented by information on occurrence, enzyme/disease relationships from text mining, sequences and 3D structures from other databases, and predicted enzyme location and genome annotation. Functional and structural data of more than 190 000 enzyme ligands are stored in BRENDA. New features improving the functionality and analysis tools were implemented. The human anatomy atlas CAVEman is linked to the BRENDA Tissue Ontology terms providing a connection between anatomical and functional enzyme data. Word Maps for enzymes obtained from PubMed.", "date": "2015-01-28T00:00:00Z", "citationCount": 161, "authors": [ { "name": "Chang A." }, { "name": "Schomburg I." }, { "name": "Placzek S." }, { "name": "Jeske L." }, { "name": "Ulbrich M." }, { "name": "Xiao M." }, { "name": "Sensen C.W." }, { "name": "Schomburg D." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkn820", "pmid": "18984617", "pmcid": "PMC2686525", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BRENDA, AMENDA and FRENDA the enzyme information system: New content and tools in 2009", "abstract": "The BRENDA (BRaunschweig ENzyme DAtabase) (http://www.brenda-enzymes.org) represents the largest freely available information system containing a huge amount of biochemical and molecular information on all classified enzymes as well as software tools for querying the database and calculating molecular properties. The database covers information on classification and nomenclature, reaction and specificity, functional parameters, occurrence, enzyme structure and stability, mutants and enzyme engineering, preparation and isolation, the application of enzymes, and ligand-related data. The data in BRENDA are manually curated from more than 79 000 primary literature references. Each entry is clearly linked to a literature reference, the origin organism and, where available, to the protein sequence of the enzyme protein. A new search option provides the access to protein-specific data. FRENDA (Full Reference ENzyme DAta) and AMENDA (Automatic Mining of ENzyme DAta) are additional databases created by continuously improved text-mining procedures. These databases ought to provide a complete survey on enzyme data of the literature collection of PubMed. The web service via a SOAP (Simple Object Access Protocol) interface for access to the BRENDA data has been further enhanced. © 2008 The Author(s).", "date": "2009-01-09T00:00:00Z", "citationCount": 314, "authors": [ { "name": "Chang A." }, { "name": "Scheer M." }, { "name": "Grote A." }, { "name": "Schomburg I." }, { "name": "Schomburg D." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkq1089", "pmid": "21062828", "pmcid": "PMC3013686", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BRENDA, the enzyme information system in 2011", "abstract": "The BRENDA (BRaunschweig ENzyme Database, http://www.brenda-enzymes.org) enzyme information system is the main collection of enzyme functional and property data for the scientific community. The majority of the data are manually extracted from the primary literature. The content covers information on function, structure, occurrence, preparation and application of enzymes as well as properties of mutants and engineered variants. The number of manually annotated references increased by 30% to more than 100 000, the number of ligand structures by 45% to almost 100 000. New query, analysis and data management tools were implemented to improve data processing, data presentation, data input and data access. BRENDA now provides new viewing options such as the display of the statistics of functional parameters and the 3D view of protein sequence and structure features. Furthermore a ligand summary shows comprehensive information on the BRENDA ligands. The enzymes are linked to their respective pathways and can be viewed in pathway maps. The disease text mining part is strongly enhanced. It is possible to submit new, not yet classified enzymes to BRENDA, which then are reviewed and classified by the International Union of Biochemistry and Molecular Biology. A new SBML output format of BRENDA kinetic data allows the construction of organism-specific metabolic models. © The Author(s) 2010.", "date": "2011-01-01T00:00:00Z", "citationCount": 353, "authors": [ { "name": "Scheer M." }, { "name": "Grote A." }, { "name": "Chang A." }, { "name": "Schomburg I." }, { "name": "Munaretto C." }, { "name": "Rother M." }, { "name": "Sohngen C." }, { "name": "Stelzer M." }, { "name": "Thiele J." }, { "name": "Schomburg D." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1186/1471-2105-12-329", "pmid": "21827651", "pmcid": "PMC3166944", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Development of a classification scheme for disease-related enzyme information", "abstract": "Background: BRENDA (BRaunschweig ENzyme DAtabase, http://www.brenda-enzymes.org) is a major resource for enzyme related information. First and foremost, it provides data which are manually curated from the primary literature. DRENDA (Disease RElated ENzyme information DAtabase) complements BRENDA with a focus on the automatic search and categorization of enzyme and disease related information from title and abstracts of primary publications. In a two-step procedure DRENDA makes use of text mining and machine learning methods.Results: Currently enzyme and disease related references are biannually updated as part of the standard BRENDA update. 910,897 relations of EC-numbers and diseases were extracted from titles or abstracts and are included in the second release in 2010. The enzyme and disease entity recognition has been successfully enhanced by a further relation classification via machine learning. The classification step has been evaluated by a 5-fold cross validation and achieves an F1 score between 0.802 ± 0.032 and 0.738 ± 0.033 depending on the categories and pre-processing procedures. In the eventual DRENDA content every category reaches a classification specificity of at least 96.7% and a precision that ranges from 86-98% in the highest confidence level, and 64-83% for the smallest confidence level associated with higher recall.Conclusions: The DRENDA processing chain analyses PubMed, locates references with disease-related information on enzymes and categorises their focus according to the categories causal interaction, therapeutic application, diagnostic usage and ongoing research. The categorisation gives an impression on the focus of the located references. Thus, the relation categorisation can facilitate orientation within the rapidly growing number of references with impact on diseases and enzymes. The DRENDA information is available as additional information in BRENDA. © 2011 Söhngen et al; licensee BioMed Central Ltd.", "date": "2011-08-09T00:00:00Z", "citationCount": 16, "authors": [ { "name": "Sohngen C." }, { "name": "Chang A." }, { "name": "Schomburg D." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1093/nar/gkh081", "pmid": "14681450", "pmcid": "PMC308815", "type": [ "Other" ], "version": null, "note": null, "metadata": null }, { "doi": "10.1093/nar/gks1049", "pmid": "23203881", "pmcid": "PMC3531171", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BRENDA in 2013: Integrated reactions, kinetic data, enzyme function data, improved disease classification: New options and contents in BRENDA", "abstract": "The BRENDA (BRaunschweig ENzyme DAtabase) enzyme portal (http://www.brenda-enzymes.org) is the main information system of functional biochemical and molecular enzyme data and provides access to seven interconnected databases. BRENDA contains 2.7 million manually annotated data on enzyme occurrence, function, kinetics and molecular properties. Each entry is connected to a reference and the source organism. Enzyme ligands are stored with their structures and can be accessed via their names, synonyms or via a structure search. FRENDA (Full Reference ENzyme DAta) and AMENDA (Automatic Mining of ENzyme DAta) are based on text mining methods and represent a complete survey of PubMed abstracts with information on enzymes in different organisms, tissues or organelles. The supplemental database DRENDA provides more than 910000 new EC number-disease relations in more than 510 000 references from automatic search and a classification of enzyme-disease-related information. KENDA (Kinetic ENzyme DAta), a new amendment extracts and displays kinetic values from PubMed abstracts. The integration of the EnzymeDetector offers an automatic comparison, evaluation and prediction of enzyme function annotations for prokaryotic genomes. The biochemical reaction database BKM-react contains non-redundant enzyme-catalysed and spontaneous reactions and was developed to facilitate and accelerate the construction of biochemical models. © The Author(s) 2012.", "date": "2013-01-01T00:00:00Z", "citationCount": 347, "authors": [ { "name": "Schomburg I." }, { "name": "Chang A." }, { "name": "Placzek S." }, { "name": "Sohngen C." }, { "name": "Rother M." }, { "name": "Lang M." }, { "name": "Munaretto C." }, { "name": "Ulas S." }, { "name": "Stelzer M." }, { "name": "Grote A." }, { "name": "Scheer M." }, { "name": "Schomburg D." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1016/s0968-0004(01)02027-8", "pmid": "11796225", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BRENDA: A resource for enzyme data and metabolic information", "abstract": "BRENDA (BRaunschweig ENzyme DAtabase), founded in 1987 by Dietmar Schomburg, is a comprehensive protein function database, containing enzymatic and metabolic information extracted from the primary literature. Presently, the database holds data on more than 40 000 enzymes and 4460 different organisms, and includes information about enzyme -ligand relationships with numerous chemical compounds. The collection of molecular and biochemical information in BRENDA provides a fundamental resource for research in biotechnology, pharmacology, medicinal diagnostics, enzyme mechanics, and metabolism. BRENDA is accessible free of charge to the academic community at http://www.brenda.uni-koeln.de/; commercial users need a license available from http://www.science-factory.com/.", "date": "2002-01-01T00:00:00Z", "citationCount": 159, "authors": [ { "name": "Schomburg I." }, { "name": "Chang A." }, { "name": "Hofmann O." }, { "name": "Ebeling C." }, { "name": "Ehrentreich F." }, { "name": "Schomburg D." } ], "journal": "Trends in Biochemical Sciences" } }, { "doi": "10.1093/nar/gkl972", "pmid": "17202167", "pmcid": "PMC1899097", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BRENDA, AMENDA and FRENDA: The enzyme information system in 2007", "abstract": "The BRENDA (BRaunschweig ENzyme DAtabase) enzyme information system (http://www.brenda.uni-koeln.de) is the largest publicly available enzyme information system worldwide. The major parts of its contents are manually extracted from primary literature. It is not restricted to specific groups of enzymes, but includes information on all identified enzymes irrespective of the enzyme's source. The range of data encompasses functional, structural, sequence, localisation, disease-related, isolation, stability information on enzyme and ligand-related data. Each single entry is linked to the enzyme source and to a literature reference. Recently the data repository was complemented by text-mining data in AMENDA (Automatic Mining of ENzyme DAta) and FRENDA (Full Reference ENzyme DAta). A genome browser, membrane protein prediction and full-text search capacities were added. The newly implemented web service provides instant access to the data for programmers via a SOAP (Simple Object Access Protocol) interface. The BRENDA data can be downloaded in the form of a text file from the beginning of 2007. © 2007 Oxford University Press.", "date": "2007-01-01T00:00:00Z", "citationCount": 137, "authors": [ { "name": "Barthelmes J." }, { "name": "Ebeling C." }, { "name": "Chang A." }, { "name": "Schomburg I." }, { "name": "Schomburg D." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/30.1.47", "pmid": "11752250", "pmcid": "PMC99121", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BRENDA, enzyme data and metabolic information", "abstract": "BRENDA is a comprehensive relational database on functional and molecular information of enzymes, based on primary literature. The database contains information extracted and evaluated from approximately 46 000 references, holding data of at least 40 000 different enzymes from more than 6900 different organisms, classified in approximately 3900 EC numbers. BRENDA is an important tool for biochemical and medical research covering information on properties of all classified enzymes, including data on the occurrence, catalyzed reaction, kinetics, substrates/products, inhibitors, cofactors, activators, structure and stability. All data are connected to literature references which in turn are linked to PubMed. The data and information provide a fundamental tool for research of enzyme mechanisms, metabolic pathways, the evolution of metabolism and, furthermore, for medicinal diagnostics and pharmaceutical research. The database is a resource for data of enzymes, classified according to the EC system of the IUBMB Enzyme Nomenclature Committee, and the entries are cross-referenced to other databases, i.e. organism classification, protein sequence, protein structure and literature references. BRENDA provides an academic web access at http://www.brenda.uni-koeln.de.", "date": "2002-01-01T00:00:00Z", "citationCount": 384, "authors": [ { "name": "Schomburg I." }, { "name": "Chang A." }, { "name": "Schomburg D." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkq968", "pmid": "21030441", "pmcid": "PMC3013802", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "The BRENDA Tissue Ontology (BTO): The first all-integrating ontology of all organisms for enzyme sources", "abstract": "BTO, the BRENDA Tissue Ontology (http://www.BTO.brenda-enzymes.org) represents a comprehensive structured encyclopedia of tissue terms. The project started in 2003 to create a connection between the enzyme data collection of the BRENDA enzyme database and a structured network of source tissues and cell types. Currently, BTO contains more than 4600 different anatomical structures, tissues, cell types and cell lines, classified under generic categories corresponding to the rules and formats of the Gene Ontology Consortium and organized as a directed acyclic graph (DAG). Most of the terms are endowed with comments on their derivation or definitions. The content of the ontology is constantly curated with ̃1000 new terms each year. Four different types of relationships between the terms are implemented. A versatile web interface with several search and navigation functionalities allows convenient online access to the BTO and to the enzymes isolated from the tissues. Important areas of applications of the BTO terms are the detection of enzymes in tissues and the provision of a solid basis for text-mining approaches in this field. It is widely used by lab scientists, curators of genomic and biochemical databases and bioinformaticians. The BTO is freely available at http://www.obofoundry.org. © The Author(s) 2010.", "date": "2011-01-01T00:00:00Z", "citationCount": 141, "authors": [ { "name": "Gremse M." }, { "name": "Chang A." }, { "name": "Schomburg I." }, { "name": "Grote A." }, { "name": "Scheer M." }, { "name": "Ebeling C." }, { "name": "Schomburg D." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "BMBF", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Funding agency", "typeRole": [ "Contributor" ], "note": null }, { "name": null, "email": "contact@brenda-enzymes.org", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures", "email": null, "url": "https://www.dsmz.de/", "orcidid": null, "gridid": "grid.420081.f", "rorid": "02tyer376", "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "matkrull", "additionDate": "2016-02-03T14:20:28Z", "lastUpdate": "2025-01-27T14:31:05.585156Z", "editPermission": { "type": "group", "authors": [ "AJaede", "juh22", "lje" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "TYGS", "description": "Automated high-throughput platform for state-of-the-art genome-based taxonomy.", "homepage": "https://tygs.dsmz.de", "biotoolsID": "TYGS", "biotoolsCURIE": "biotools:TYGS", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Deposition" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" }, { "uri": "http://edamontology.org/operation_0544", "term": "Phylogenetic species tree construction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_0084", "term": "Phylogeny" }, { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "Unlicense", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://tygs.dsmz.de/faqs", "type": [ "FAQ" ], "note": null } ], "publication": [ { "doi": "10.1038/S41467-019-10210-3", "pmid": "31097708", "pmcid": "PMC6522516", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "TYGS is an automated high-throughput platform for state-of-the-art genome-based taxonomy", "abstract": "© 2019, The Author(s).Microbial taxonomy is increasingly influenced by genome-based computational methods. Yet such analyses can be complex and require expert knowledge. Here we introduce TYGS, the Type (Strain) Genome Server, a user-friendly high-throughput web server for genome-based prokaryote taxonomy, connected to a large, continuously growing database of genomic, taxonomic and nomenclatural information. It infers genome-scale phylogenies and state-of-the-art estimates for species and subspecies boundaries from user-defined and automatically determined closest type genome sequences. TYGS also provides comprehensive access to nomenclature, synonymy and associated taxonomic literature. Clinically important examples demonstrate how TYGS can yield new insights into microbial classification, such as evidence for a species-level separation of previously proposed subspecies of Salmonella enterica. TYGS is an integrated approach for the classification of microbes that unlocks novel scientific approaches to microbiologists worldwide and is particularly helpful for the rapidly expanding field of genome-based taxonomic descriptions of new genera, species or subspecies.", "date": "2019-12-01T00:00:00Z", "citationCount": 409, "authors": [ { "name": "Meier-Kolthoff J.P." }, { "name": "Goker M." } ], "journal": "Nature Communications" } } ], "credit": [ { "name": "Jan P. Meier-Kolthoff", "email": "jan.meier-kolthoff@dsmz.de", "url": null, "orcidid": "https://orcid.org/0000-0001-9105-9814", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "mgoeker", "additionDate": "2019-08-09T13:13:30Z", "lastUpdate": "2025-01-23T15:00:45.502376Z", "editPermission": { "type": "group", "authors": [ "mgoeker" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BacDive", "description": "BacDive (The Bacterial Diversity Database) is the worldwide largest database for standardized bacterial and archaeal strain-level information. Its mission is to mobilize and integrate research data on strain level from diverse sources and make it freely accessible.\n\nBacDive is a comprehensive resource containing diverse data on bacterial and archaeal strains, including taxonomy, morphology, physiology, sampling and environmental data and sequence information.", "homepage": "https://bacdive.dsmz.de", "biotoolsID": "bacdive", "biotoolsCURIE": "biotools:bacdive", "version": [], "otherID": [], "relation": [ { "biotoolsID": "bacdive_ws", "type": "includes" }, { "biotoolsID": "d3hub", "type": "includedIn" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1045", "term": "Species name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2912", "term": "Strain accession" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1179", "term": "NCBI taxonomy ID" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2379", "term": "Strain identifier" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2093", "term": "Data reference" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_1872", "term": "Taxonomic classification" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_2912", "term": "Strain accession" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_1179", "term": "NCBI taxonomy ID" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_2087", "term": "Molecular property" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_0912", "term": "Nucleic acid property" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_3723", "term": "Morphology parameter" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_3722", "term": "Physiology parameter" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_3721", "term": "Isolation source" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_3720", "term": "Geographic location" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_3719", "term": "Biosafety classification" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] }, { "data": { "uri": "http://edamontology.org/data_3718", "term": "Pathogenicity report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] } ], "note": "The BacDive portal offers several search options:\nSimple Search / Smart Search \nAdvanced Search\nIsolation Source Search\nAPI test finder\nTAXplorer\nSpecial collections", "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3050", "term": "Biodiversity" }, { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_3339", "term": "Microbial collection" }, { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "PHP" ], "license": "CC-BY-4.0", "collectionID": [ "de.NBI", "DSMZ Digital Diversity", "Core Data Resources", "de.NBI-biodata", "ELIXIR-DE" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access", "elixirPlatform": [ "Data" ], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://bacdive.dsmz.de/mailinglist/subscribe", "type": [ "Mailing list" ], "note": null }, { "url": "https://bacdive.dsmz.de/contact", "type": [ "Helpdesk" ], "note": null }, { "url": "https://bsky.app/profile/bacdive.bsky.social", "type": [ "Social media" ], "note": null }, { "url": "https://www.linkedin.com/company/dsmzd3/", "type": [ "Social media" ], "note": null } ], "download": [], "documentation": [ { "url": "https://bacdive.dsmz.de/about", "type": [ "Terms of use", "Citation instructions" ], "note": null }, { "url": "https://bacdive.dsmz.de/tutorials", "type": [ "Training material" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkae959", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "BacDive in 2025: the core database for prokaryotic strain data", "abstract": "In 2025, the bacterial diversity database BacDive is the leading database for strain-level bacterial and archaeal information. It has been selected as an ELIXIR Core Data Resource as well as a Global Core Biodata Resource. Since its initial release more than ten years ago, BacDive (https://bacdive.dsmz.de) has grown tremendously in content and functionalities, and is a comprehensive resource covering the phenotypic diversity of prokaryotes with data on taxonomy, morphology, physiology, cultivation, and more. The current release (2023.2) contains 2.6 million data points on 97 334 strains, reflecting an increase by 52% since the previous publication in 2021. This remarkable growth can largely be attributed to the integration of the world-wide largest collection of Analytical Profile Index (API) test results, which are now fully integrated into the database and searchable. A novel BacDive knowledge graph provides powerful search options through a SPARQL endpoint, including the possibility for federated searches across multiple data sources. The high-quality data provided by BacDive is increasingly being used for the training of artificial intelligence models and resulting genome-based predictions with high confidence are now used to fill content gaps in the database.", "date": "2025-01-06T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Schober I." }, { "name": "Koblitz J." }, { "name": "Carbasse J.S." }, { "name": "Ebeling C." }, { "name": "Schmidt M.L." }, { "name": "Podstawka A." }, { "name": "Gupta R." }, { "name": "Ilangovan V." }, { "name": "Chamanara J." }, { "name": "Overmann J." }, { "name": "Reimer L.C." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkab961", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BacDive in 2022: The knowledge base for standardized bacterial and archaeal data", "abstract": "The bacterial metadatabase BacDive (https://bacdive.dsmz.de) has developed into a leading database for standardized prokaryotic data on strain level. With its current release (07/2021) the database offers information for 82 892 bacterial and archaeal strains covering taxonomy, morphology, cultivation, metabolism, origin, and sequence information within 1048 data fields. By integrating high-quality data from additional culture collections as well as detailed information from species descriptions, the amount of data provided has increased by 30% over the past three years. A newly developed query builder tool in the advanced search now allows complex database queries. Thereby bacterial strains can be systematically searched based on combinations of their attributes, e.g. growth and metabolic features for biotechnological applications or to identify gaps in the present knowledge about bacteria. A new interactive dashboard provides a statistic overview over the most important data fields. Additional new features are improved genomic sequence data, integrated NCBI TaxIDs and links to BacMedia, the new sister database on cultivation media. To improve the findability and interpretation of data through search engines, data in BacDive are annotated with bioschemas.org terms.", "date": "2022-01-07T00:00:00Z", "citationCount": 106, "authors": [ { "name": "Reimer L.C." }, { "name": "Sarda Carbasse J." }, { "name": "Koblitz J." }, { "name": "Ebeling C." }, { "name": "Podstawka A." }, { "name": "Overmann J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gky879", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BacDive in 2019: Bacterial phenotypic data for High-throughput biodiversity analysis", "abstract": "The bacterial metadatabase BacDive (http://bacdive.dsmz.de) has become a comprehensive resource for structured data on the taxonomy, morphology, physiology, cultivation, isolation and molecular data of prokaryotes. With its current release (7/2018) the database offers information for 63 669 bacterial and archaeal strains including 12 715 type strains. During recent developments of BacDive, the enrichment of information on existing strains was prioritized. This has resulted in a 146% increase of database content over the past three years. Especially rich datasets were integrated from 4782 manual annotated species descriptions in the International Journal of Systematic and Evolutionary Microbiology which yielded standardized phenotypic data for 5468 type strains. Another important improvement of content was achieved through the mobilization of 8977 Analytical Profile Index (API ® ) test results that constitute physiological data for the identification of 5237 strains. BacDive offers a unique API ® data collection with respect to size and diversity. In addition, data on fatty acid profiles and antibiotic susceptibility tests were integrated. A revised graphical user interface and new search tools such as the API ® test finder, the TAXplorer, or the Microbial Isolation Source Search significantly improve the user experience.", "date": "2019-01-08T00:00:00Z", "citationCount": 132, "authors": [ { "name": "Reimer L.C." }, { "name": "Vetcininova A." }, { "name": "Carbasse J.S." }, { "name": "Sohngen C." }, { "name": "Gleim D." }, { "name": "Ebeling C." }, { "name": "Overmann J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1016/j.jbiotec.2017.05.004", "pmid": "28487186", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Mobilization and integration of bacterial phenotypic data—Enabling next generation biodiversity analysis through the BacDive metadatabase", "abstract": "Microbial data and metadata are scattered throughout the scientific literature, databases and unpublished lab notes and thereby often are difficult to access. Hot spots of (meta)data are internal descriptions of culture collections and initial descriptions of novel taxa in primary literature. Here we describe three exemplary mobilization projects which yielded metadata published through the prokaryotic metadatabase BacDive. The Reichenbach collection of myxobacteria includes information on 12,535 typewritten index cards which were digitized. A total of 37,156 data points were extracted by text mining. In the second mobilization project, Analytical Profile Index (API) tests on paper forms were targeted. Overall 6820 API tests were digitized, which provide physiological data of 4524 microbial strains. Thirdly, the extraction of metadata from 523 new species descriptions of the International Journal of Systematic and Evolutionary Microbiology, yielding 35,651 data points, is described. All data sets were integrated and published in BacDive. Thereby these metadata not only became accessible and searchable but were also linked to strain taxonomy, isolation source, cultivation condition, and molecular biology data.", "date": "2017-11-10T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Reimer L.C." }, { "name": "Sohngen C." }, { "name": "Vetcininova A." }, { "name": "Overmann J." } ], "journal": "Journal of Biotechnology" } }, { "doi": "10.1093/nar/gkv983", "pmid": "26424852", "pmcid": "PMC4702946", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BacDive - The Bacterial Diversity Metadatabase in 2016", "abstract": "BacDive-the Bacterial Diversity Metadatabase (http://bacdive.dsmz.de) provides strain-linked information about bacterial and archaeal biodiversity. The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology. The majority of data is manually annotated and curated. Currently (with release 9/2015), BacDive covers 53 978 strains. Newly implemented RESTful web services provide instant access to the content in machinereadable XML and JSON format. Besides an overall increase of data content, BacDive offers new data fields and features, e.g. the search for gene names, plasmids or 16S rRNA in the advanced search, as well as improved linkage of entries to external life science web resources.", "date": "2016-01-01T00:00:00Z", "citationCount": 44, "authors": [ { "name": "Sohngen C." }, { "name": "Podstawka A." }, { "name": "Bunk B." }, { "name": "Gleim D." }, { "name": "Vetcininova A." }, { "name": "Reimer L.C." }, { "name": "Ebeling C." }, { "name": "Pendarovski C." }, { "name": "Leibniz J.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkt1058", "pmid": "24214959", "pmcid": "PMC3965005", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BacDive - The Bacterial Diversity Metadatabase", "abstract": "BacDive - the Bacterial Diversity Metadatabase (http://bacdive.dsmz.de) merges detailed strain-linked information on the different aspects of bacterial and archaeal biodiversity. Currently (release 9/2013), BacDive contains entries for 23 458 strains and provides information on their taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology. Where available, links to access the respective biological resources are given. The majority of the BacDive data is manually annotated and curated. The BacDive portal offers an easy-to-use simple search and in addition powerful advanced search functionalities allowing to combine more than 30 search fields for text and numerical data. The user can compile individual sets of strains to a download selection that can easily be imported into nearly all spreadsheet applications. © 2013 The Author(s). Published by Oxford University Press.", "date": "2014-01-01T00:00:00Z", "citationCount": 33, "authors": [ { "name": "Sohngen C." }, { "name": "Bunk B." }, { "name": "Podstawka A." }, { "name": "Gleim D." }, { "name": "Overmann J." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH", "email": null, "url": "https://www.dsmz.de/", "orcidid": null, "gridid": null, "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "contact@bacdive.de", "url": "https://bacdive.dsmz.de/contact", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "lorenz.reimer", "additionDate": "2016-10-10T12:39:00Z", "lastUpdate": "2025-01-23T07:43:33.828764Z", "editPermission": { "type": "group", "authors": [ "JKoblitz", "Joaquim", "isabelschober" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BacDive API", "description": "The API for retrieving BacDive data in machine-readable JSON format. BacDive is the Bacterial Diversity Database and provides strain-linked information about bacterial and archaeal biodiversity. The API offers several possibilities to query detailed strain information.", "homepage": "https://api.bacdive.dsmz.de/", "biotoolsID": "bacdive_ws", "biotoolsCURIE": "biotools:bacdive_ws", "version": [], "otherID": [], "relation": [ { "biotoolsID": "bacdive", "type": "includedIn" }, { "biotoolsID": "d3hub", "type": "includedIn" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1048", "term": "Database ID" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] } ], "note": "curl \"https://api.bacdive.dsmz.de/example/fetch/{bacdive_id}\"", "cmd": "curl \"https://api.bacdive.dsmz.de/example/fetch/{bacdive_id}\"" }, { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1045", "term": "Species name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1870", "term": "Genus name" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2379", "term": "Strain identifier" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2787", "term": "NCBI genome accession" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1048", "term": "Database ID" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web API" ], "topic": [ { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_3339", "term": "Microbial collection" }, { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [], "license": "CC-BY-4.0", "collectionID": [ "de.NBI", "DSMZ Digital Diversity", "Core Data Resources" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access (with restrictions)", "elixirPlatform": [ "Data" ], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://bacdive.dsmz.de/", "type": [ "Service" ], "note": null }, { "url": "https://bsky.app/profile/bacdive.bsky.social", "type": [ "Social media" ], "note": null } ], "download": [], "documentation": [ { "url": "https://api.bacdive.dsmz.de/", "type": [ "API documentation", "Citation instructions" ], "note": null }, { "url": "https://bacdive.dsmz.de/tutorials", "type": [ "Training material" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkae959", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "BacDive in 2025: the core database for prokaryotic strain data", "abstract": "In 2025, the bacterial diversity database BacDive is the leading database for strain-level bacterial and archaeal information. It has been selected as an ELIXIR Core Data Resource as well as a Global Core Biodata Resource. Since its initial release more than ten years ago, BacDive (https://bacdive.dsmz.de) has grown tremendously in content and functionalities, and is a comprehensive resource covering the phenotypic diversity of prokaryotes with data on taxonomy, morphology, physiology, cultivation, and more. The current release (2023.2) contains 2.6 million data points on 97 334 strains, reflecting an increase by 52% since the previous publication in 2021. This remarkable growth can largely be attributed to the integration of the world-wide largest collection of Analytical Profile Index (API) test results, which are now fully integrated into the database and searchable. A novel BacDive knowledge graph provides powerful search options through a SPARQL endpoint, including the possibility for federated searches across multiple data sources. The high-quality data provided by BacDive is increasingly being used for the training of artificial intelligence models and resulting genome-based predictions with high confidence are now used to fill content gaps in the database.", "date": "2025-01-06T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Schober I." }, { "name": "Koblitz J." }, { "name": "Carbasse J.S." }, { "name": "Ebeling C." }, { "name": "Schmidt M.L." }, { "name": "Podstawka A." }, { "name": "Gupta R." }, { "name": "Ilangovan V." }, { "name": "Chamanara J." }, { "name": "Overmann J." }, { "name": "Reimer L.C." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkab961", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BacDive in 2022: The knowledge base for standardized bacterial and archaeal data", "abstract": "The bacterial metadatabase BacDive (https://bacdive.dsmz.de) has developed into a leading database for standardized prokaryotic data on strain level. With its current release (07/2021) the database offers information for 82 892 bacterial and archaeal strains covering taxonomy, morphology, cultivation, metabolism, origin, and sequence information within 1048 data fields. By integrating high-quality data from additional culture collections as well as detailed information from species descriptions, the amount of data provided has increased by 30% over the past three years. A newly developed query builder tool in the advanced search now allows complex database queries. Thereby bacterial strains can be systematically searched based on combinations of their attributes, e.g. growth and metabolic features for biotechnological applications or to identify gaps in the present knowledge about bacteria. A new interactive dashboard provides a statistic overview over the most important data fields. Additional new features are improved genomic sequence data, integrated NCBI TaxIDs and links to BacMedia, the new sister database on cultivation media. To improve the findability and interpretation of data through search engines, data in BacDive are annotated with bioschemas.org terms.", "date": "2022-01-07T00:00:00Z", "citationCount": 106, "authors": [ { "name": "Reimer L.C." }, { "name": "Sarda Carbasse J." }, { "name": "Koblitz J." }, { "name": "Ebeling C." }, { "name": "Podstawka A." }, { "name": "Overmann J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gky879", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BacDive in 2019: Bacterial phenotypic data for High-throughput biodiversity analysis", "abstract": "The bacterial metadatabase BacDive (http://bacdive.dsmz.de) has become a comprehensive resource for structured data on the taxonomy, morphology, physiology, cultivation, isolation and molecular data of prokaryotes. With its current release (7/2018) the database offers information for 63 669 bacterial and archaeal strains including 12 715 type strains. During recent developments of BacDive, the enrichment of information on existing strains was prioritized. This has resulted in a 146% increase of database content over the past three years. Especially rich datasets were integrated from 4782 manual annotated species descriptions in the International Journal of Systematic and Evolutionary Microbiology which yielded standardized phenotypic data for 5468 type strains. Another important improvement of content was achieved through the mobilization of 8977 Analytical Profile Index (API ® ) test results that constitute physiological data for the identification of 5237 strains. BacDive offers a unique API ® data collection with respect to size and diversity. In addition, data on fatty acid profiles and antibiotic susceptibility tests were integrated. A revised graphical user interface and new search tools such as the API ® test finder, the TAXplorer, or the Microbial Isolation Source Search significantly improve the user experience.", "date": "2019-01-08T00:00:00Z", "citationCount": 132, "authors": [ { "name": "Reimer L.C." }, { "name": "Vetcininova A." }, { "name": "Carbasse J.S." }, { "name": "Sohngen C." }, { "name": "Gleim D." }, { "name": "Ebeling C." }, { "name": "Overmann J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1016/j.jbiotec.2017.05.004", "pmid": "28487186", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Mobilization and integration of bacterial phenotypic data—Enabling next generation biodiversity analysis through the BacDive metadatabase", "abstract": "Microbial data and metadata are scattered throughout the scientific literature, databases and unpublished lab notes and thereby often are difficult to access. Hot spots of (meta)data are internal descriptions of culture collections and initial descriptions of novel taxa in primary literature. Here we describe three exemplary mobilization projects which yielded metadata published through the prokaryotic metadatabase BacDive. The Reichenbach collection of myxobacteria includes information on 12,535 typewritten index cards which were digitized. A total of 37,156 data points were extracted by text mining. In the second mobilization project, Analytical Profile Index (API) tests on paper forms were targeted. Overall 6820 API tests were digitized, which provide physiological data of 4524 microbial strains. Thirdly, the extraction of metadata from 523 new species descriptions of the International Journal of Systematic and Evolutionary Microbiology, yielding 35,651 data points, is described. All data sets were integrated and published in BacDive. Thereby these metadata not only became accessible and searchable but were also linked to strain taxonomy, isolation source, cultivation condition, and molecular biology data.", "date": "2017-11-10T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Reimer L.C." }, { "name": "Sohngen C." }, { "name": "Vetcininova A." }, { "name": "Overmann J." } ], "journal": "Journal of Biotechnology" } }, { "doi": "10.1093/nar/gkv983", "pmid": "26424852", "pmcid": "PMC4702946", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BacDive - The Bacterial Diversity Metadatabase in 2016", "abstract": "BacDive-the Bacterial Diversity Metadatabase (http://bacdive.dsmz.de) provides strain-linked information about bacterial and archaeal biodiversity. The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology. The majority of data is manually annotated and curated. Currently (with release 9/2015), BacDive covers 53 978 strains. Newly implemented RESTful web services provide instant access to the content in machinereadable XML and JSON format. Besides an overall increase of data content, BacDive offers new data fields and features, e.g. the search for gene names, plasmids or 16S rRNA in the advanced search, as well as improved linkage of entries to external life science web resources.", "date": "2016-01-01T00:00:00Z", "citationCount": 44, "authors": [ { "name": "Sohngen C." }, { "name": "Podstawka A." }, { "name": "Bunk B." }, { "name": "Gleim D." }, { "name": "Vetcininova A." }, { "name": "Reimer L.C." }, { "name": "Ebeling C." }, { "name": "Pendarovski C." }, { "name": "Leibniz J.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkt1058", "pmid": "24214959", "pmcid": "PMC3965005", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "BacDive - The Bacterial Diversity Metadatabase", "abstract": "BacDive - the Bacterial Diversity Metadatabase (http://bacdive.dsmz.de) merges detailed strain-linked information on the different aspects of bacterial and archaeal biodiversity. Currently (release 9/2013), BacDive contains entries for 23 458 strains and provides information on their taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology. Where available, links to access the respective biological resources are given. The majority of the BacDive data is manually annotated and curated. The BacDive portal offers an easy-to-use simple search and in addition powerful advanced search functionalities allowing to combine more than 30 search fields for text and numerical data. The user can compile individual sets of strains to a download selection that can easily be imported into nearly all spreadsheet applications. © 2013 The Author(s). Published by Oxford University Press.", "date": "2014-01-01T00:00:00Z", "citationCount": 33, "authors": [ { "name": "Sohngen C." }, { "name": "Bunk B." }, { "name": "Podstawka A." }, { "name": "Gleim D." }, { "name": "Overmann J." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH", "email": "hub@dsmz.de", "url": "https://dsmz.de", "orcidid": null, "gridid": null, "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "contact@bacdive.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "lorenz.reimer", "additionDate": "2016-01-28T09:14:11Z", "lastUpdate": "2025-01-22T12:15:27.195571Z", "editPermission": { "type": "group", "authors": [ "isabelschober", "Joaquim" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "MMTB", "description": "The Metano Metabolic Modeling Toolbox.", "homepage": "https://mmtb.brenda-enzymes.org/", "biotoolsID": "mmtb", "biotoolsCURIE": "biotools:mmtb", "version": [], "otherID": [], "relation": [ { "biotoolsID": "enzymedetector", "type": "includes" }, { "biotoolsID": "bkmsreact", "type": "includes" }, { "biotoolsID": "metano", "type": "includes" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2526", "term": "Text data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3869", "term": "Simulation" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_3391", "term": "Omics" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [ "Python" ], "license": "CC-BY-4.0", "collectionID": [ "DSMZ Digital Diversity" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://mmtb.brenda-enzymes.org/metano/install", "type": "Downloads page", "note": null, "version": null } ], "documentation": [ { "url": "https://mmtb.brenda-enzymes.org/help", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.3390/metabo11020113", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The metano modeling toolbox MMTB: An intuitive, web-based toolbox introduced by two use cases", "abstract": "Genome-scale metabolic models are of high interest in a number of different research fields. Flux balance analysis (FBA) and other mathematical methods allow the prediction of the steady-state behavior of metabolic networks under different environmental conditions. However, many existing applications for flux optimizations do not provide a metabolite-centric view on fluxes. Metano is a standalone, open-source toolbox for the analysis and refinement of metabolic models. While flux distributions in metabolic networks are predominantly analyzed from a reaction-centric point of view, the Metano methods of split-ratio analysis and metabolite flux minimization also allow a metabolite-centric view on flux distributions. In addition, we present MMTB (mmtb.brendaenzymes.org), a web-based toolbox for metabolic modeling including a user-friendly interface to Metano methods. MMTB assists during bottom-up construction of metabolic models by integrating reaction and enzymatic annotation data from different databases. Furthermore, MMTB is especially designed for non-experienced users by providing an intuitive interface to the most commonly used modeling methods and offering novel visualizations. Additionally, MMTB allows users to upload their models, which can in turn be explored and analyzed by the community. We introduce MMTB by two use cases, involving a published model of Corynebacterium glutamicum and a newly created model of Phaeobacter inhibens.", "date": "2021-02-01T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Koblitz J." }, { "name": "Will S.E." }, { "name": "Riemer S.A." }, { "name": "Ulas T." }, { "name": "Neumann-Schaal M." }, { "name": "Schomburg D." } ], "journal": "Metabolites" } } ], "credit": [ { "name": "Julia Koblitz", "email": "julia.koblitz@dsmz.de", "url": "https://research.dsmz.de/person/651cecd8b3c97f11cc28cfc2", "orcidid": "https://orcid.org/0000-0002-7260-2129", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null }, { "name": "Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH", "email": "hub@dsmz.de", "url": "https://dsmz.de", "orcidid": null, "gridid": null, "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "JKoblitz", "additionDate": "2025-01-22T10:00:56.561701Z", "lastUpdate": "2025-01-22T10:09:15.144513Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SILVA rRNA database", "description": "SILVA provides comprehensive, quality checked and regularly updated datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukaryota).", "homepage": "http://www.arb-silva.de", "biotoolsID": "silva", "biotoolsCURIE": "biotools:silva", "version": [], "otherID": [ { "value": "RRID:SCR_006423", "type": "rrid", "version": null } ], "relation": [ { "biotoolsID": "silvangs", "type": "usedBy" }, { "biotoolsID": "d3hub", "type": "includedIn" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_1868", "term": "Taxon" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_1046", "term": "Strain name" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_1088", "term": "Article ID" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_2909", "term": "Organism name" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2955", "term": "Sequence report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] }, { "data": { "uri": "http://edamontology.org/data_1383", "term": "Sequence alignment (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_2333", "term": "Binary format" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] } ], "note": "The search and retrieval functions of the SILVA website can be used to build custom subsets of sequences. In addition to simple searches e.g. for accession numbers, organism names, taxonomic entities, or publication DOI/PubMed IDs, complex queries over several database fields using constraints such as sequence length or quality values are possible. The results can be sorted according to accession numbers, organism names, sequence length, sequence and alignment quality and Pintail values. The search results show accession number, organism name, sequence length, sequence quality values, taxonomic classifications, and links to view the full sequence record on SILVA and on ENA. Sequences found via search and added to download cart can be downloaded as FASTA and ARB files.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0292", "term": "Sequence alignment" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Sequence alignment (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_2333", "term": "Binary format" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] } ], "note": "SILVA Incremental Aligner (SINA) is used to align the rRNA gene databases provided by SILVA, as well as user submitted sequences. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. Aligned sequences can be dowloaded as FASTA or ARB files", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Sequence alignment (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_2333", "term": "Binary format" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] }, { "data": { "uri": "http://edamontology.org/data_1872", "term": "Taxonomic classification" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "SINA can also operate as a taxonomic classification tool. It uses the search result to derive a classification with the LCA (lowest common ancestor) method. Each query sequence is assigned the shared part of the classifications of the search results. Aligned sequences can be dowloaded as FASTA or ARB files Taxonomic classification results can be downloaded as csv files.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2419", "term": "Primer and probe design" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1207", "term": "nucleotide" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "The SILVA Probe Match and Evaluation Tool detects and displays all occurrences of a given probe or primer sequence in the SILVA datasets. TestPrime allows you to evaluate the performance of primer pairs by running an in silico PCR on the SILVA databases. From the results of the PCR, TestPrime computes coverages for each taxonomic group in all of the taxonomies offered by SILVA.", "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" }, { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_3050", "term": "Biodiversity" }, { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" }, { "uri": "http://edamontology.org/topic_0632", "term": "Probes and primers" } ], "operatingSystem": [], "language": [], "license": "CC-BY-4.0", "collectionID": [ "de.NBI", "de.NBI-biodata", "DSMZ Digital Diversity" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data" ], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://www.arb-silva.de/browser/", "type": [ "Service" ], "note": "SILVA Taxonomy Browser" }, { "url": "https://www.arb-silva.de/search/", "type": [ "Service" ], "note": "SILVA metadata search" }, { "url": "https://www.arb-silva.de/aligner/", "type": [ "Service" ], "note": "ACT: Alignment, Classification and Tree Service" }, { "url": "https://www.arb-silva.de/search/testprobe/", "type": [ "Service" ], "note": "SILVA Probe Match and Evaluation Tool" }, { "url": "https://www.arb-silva.de/search/testprime/", "type": [ "Service" ], "note": "SILVA Primer Evaluation Tool" }, { "url": "https://treeviewer.arb-silva.de/", "type": [ "Service" ], "note": "Web-based viewer for the SILVA guide trees" } ], "download": [ { "url": "https://www.arb-silva.de/download/archive/", "type": "Downloads page", "note": "SILVA dataset archive", "version": null } ], "documentation": [ { "url": "https://www.arb-silva.de/silva-license-information/", "type": [ "Terms of use" ], "note": null }, { "url": "https://www.arb-silva.de/contact/", "type": [ "Citation instructions" ], "note": null }, { "url": "http://www.arb-silva.de/documentation/", "type": [ "General" ], "note": null }, { "url": "https://www.arb-silva.de/documentation/faqs/", "type": [ "FAQ" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gks1219", "pmid": "23193283", "pmcid": "PMC3531112", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3194 778 small subunit and 288717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches. © The Author(s) 2012.", "date": "2013-01-01T00:00:00Z", "citationCount": 20831, "authors": [ { "name": "Quast C." }, { "name": "Pruesse E." }, { "name": "Yilmaz P." }, { "name": "Gerken J." }, { "name": "Schweer T." }, { "name": "Yarza P." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkt1209", "pmid": "24293649", "pmcid": "PMC3965112", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "The SILVA and \"all-species Living Tree Project (LTP)\" taxonomic frameworks", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive resource for up-to-date quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. SILVA provides a manually curated taxonomy for all three domains of life, based on representative phylogenetic trees for the small- and large-subunit rRNA genes. This article describes the improvements the SILVA taxonomy has undergone in the last 3 years. Specifically we are focusing on the curation process, the various resources used for curation and the comparison of the SILVA taxonomy with Greengenes and RDP-II taxonomies. Our comparisons not only revealed a reasonable overlap between the taxa names, but also points to significant differences in both names and numbers of taxa between the three resources. © 2013 The Author(s). Published by Oxford University Press.", "date": "2014-01-01T00:00:00Z", "citationCount": 2372, "authors": [ { "name": "Yilmaz P." }, { "name": "Parfrey L.W." }, { "name": "Yarza P." }, { "name": "Gerken J." }, { "name": "Pruesse E." }, { "name": "Quast C." }, { "name": "Schweer T." }, { "name": "Peplies J." }, { "name": "Ludwig W." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkm864", "pmid": "17947321", "pmcid": "PMC2175337", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB", "abstract": "Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs. © 2007 The Author(s).", "date": "2007-12-01T00:00:00Z", "citationCount": 5145, "authors": [ { "name": "Pruesse E." }, { "name": "Quast C." }, { "name": "Knittel K." }, { "name": "Fuchs B.M." }, { "name": "Ludwig W." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/bts252", "pmid": "22556368", "pmcid": "PMC3389763", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes", "abstract": "Motivation: In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements.Results: In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. © The Author(s) 2012. Published by Oxford University Press.", "date": "2012-07-01T00:00:00Z", "citationCount": 2352, "authors": [ { "name": "Pruesse E." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Bioinformatics" } }, { "doi": "10.1016/j.jbiotec.2017.06.1198", "pmid": "28648396", "pmcid": null, "type": [ "Review" ], "version": null, "note": null, "metadata": { "title": "25 years of serving the community with ribosomal RNA gene reference databases and tools", "abstract": "SILVA (lat. forest) is a comprehensive web resource, providing services around up to date, high-quality datasets of aligned ribosomal RNA gene (rDNA) sequences from the Bacteria, Archaea, and Eukaryota domains. SILVA dates back to the year 1991 when Dr. Wolfgang Ludwig from the Technical University Munich started the integrated software workbench ARB (lat. tree) to support high-quality phylogenetic inference and taxonomy based on the SSU and LSU rDNA marker genes. At that time, the ARB project maintained both, the sequence reference datasets and the software package for data analysis. In 2005, with the massive increase of DNA sequence data, the maintenance of the software system ARB and the corresponding rRNA databases SILVA was split between Munich and the Microbial Genomics and Bioinformatics Research Group in Bremen. ARB has been continuously developed to include new features and improve the usability of the workbench. Thousands of users worldwide appreciate the seamless integration of common analysis tools under a central graphical user interface, in combination with its versatility. The first SILVA release was deployed in February 2007 based on the EMBL-EBI/ENA release 89. Since then, full SILVA releases offering the database content in various flavours are published at least annually, complemented by intermediate web-releases where only the SILVA web dataset is updated. SILVA is the only rDNA database project worldwide where special emphasis is given to the consistent naming of clades of uncultivated (environmental) sequences, where no validly described cultivated representatives are available. Also exclusive for SILVA is the maintenance of both comprehensive aligned 16S/18S rDNA and 23S/28S rDNA sequence datasets. Furthermore, the SILVA alignments and trees were designed to include Eukaryota, another unique feature among rDNA databases. With the termination of the European Ribosomal RNA Database Project in 2007, the SILVA database has become the authoritative rDNA database project for Europe. The application spectrum of ARB and SILVA ranges from biodiversity analysis, medical diagnostics, to biotechnology and quality control for academia and industry.", "date": "2017-11-10T00:00:00Z", "citationCount": 578, "authors": [ { "name": "Glockner F.O." }, { "name": "Yilmaz P." }, { "name": "Quast C." }, { "name": "Gerken J." }, { "name": "Beccati A." }, { "name": "Ciuprina A." }, { "name": "Bruns G." }, { "name": "Yarza P." }, { "name": "Peplies J." }, { "name": "Westram R." }, { "name": "Ludwig W." } ], "journal": "Journal of Biotechnology" } }, { "doi": "10.1186/s12859-017-1841-3", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SILVA tree viewer: Interactive web browsing of the SILVA phylogenetic guide trees", "abstract": "Background: Phylogenetic trees are an important tool to study the evolutionary relationships among organisms. The huge amount of available taxa poses difficulties in their interactive visualization. This hampers the interaction with the users to provide feedback for the further improvement of the taxonomic framework. Results: The SILVA Tree Viewer is a web application designed for visualizing large phylogenetic trees without requiring the download of any software tool or data files. The SILVA Tree Viewer is based on Web Geographic Information Systems (Web-GIS) technology with a PostgreSQL backend. It enables zoom and pan functionalities similar to Google Maps. The SILVA Tree Viewer enables access to two phylogenetic (guide) trees provided by the SILVA database: the SSU Ref NR99 inferred from high-quality, full-length small subunit sequences, clustered at 99% sequence identity and the LSU Ref inferred from high-quality, full-length large subunit sequences. Conclusions: The Tree Viewer provides tree navigation, search and browse tools as well as an interactive feedback system to collect any kinds of requests ranging from taxonomy to data curation and improving the tool itself.", "date": "2017-09-30T00:00:00Z", "citationCount": 28, "authors": [ { "name": "Beccati A." }, { "name": "Gerken J." }, { "name": "Quast C." }, { "name": "Yilmaz P." }, { "name": "Glockner F.O." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures", "email": "hub@dsmz.de", "url": "https://www.dsmz.de", "orcidid": null, "gridid": "grid.420081.f", "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "contact@arb-silva.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Project", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "silva", "additionDate": "2016-09-30T15:59:05Z", "lastUpdate": "2025-01-22T09:59:03.064970Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "SILVAngs", "description": "SILVAngs is a data analysis service for ribosomal RNA gene (rDNA) amplicon reads from high-throughput sequencing (next-generation sequencing (NGS)) approaches based on an automatic software pipeline. It uses the SILVA rDNA databases, taxonomies, and alignments as a reference. It facilitates the classification of rDNA reads and provides a wealth of results (tables, graphs and sequence files) for download.", "homepage": "https://www.arb-silva.de/ngs/", "biotoolsID": "silvangs", "biotoolsCURIE": "biotools:silvangs", "version": [ "1.6.2" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" }, { "uri": "http://edamontology.org/operation_2478", "term": "Nucleic acid sequence analysis" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" }, { "uri": "http://edamontology.org/operation_2428", "term": "Validation" }, { "uri": "http://edamontology.org/operation_0291", "term": "Sequence clustering" }, { "uri": "http://edamontology.org/operation_0292", "term": "Sequence alignment" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_2082", "term": "Matrix" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_1246", "term": "Sequence cluster (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_2333", "term": "Binary format" } ] } ], "note": "The pipeline accepts input data in Multi-Fasta format with each input file representing one sample. Samples that belong to one project (a transect, timeseries etc.) should be uploaded as a single SILVAngs project.", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3050", "term": "Biodiversity" }, { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "de.NBI", "de.NBI-biodata", "DSMZ Digital Diversity" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://www.arb-silva.de/ngs/service/file/?file=SILVAngs_User_Guide_15_12_15.pdf", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gks1219", "pmid": "23193283", "pmcid": "PMC3531112", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3194 778 small subunit and 288717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches. © The Author(s) 2012.", "date": "2013-01-01T00:00:00Z", "citationCount": 20831, "authors": [ { "name": "Quast C." }, { "name": "Pruesse E." }, { "name": "Yilmaz P." }, { "name": "Gerken J." }, { "name": "Schweer T." }, { "name": "Yarza P." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkt1209", "pmid": "24293649", "pmcid": "PMC3965112", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "The SILVA and \"all-species Living Tree Project (LTP)\" taxonomic frameworks", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive resource for up-to-date quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. SILVA provides a manually curated taxonomy for all three domains of life, based on representative phylogenetic trees for the small- and large-subunit rRNA genes. This article describes the improvements the SILVA taxonomy has undergone in the last 3 years. Specifically we are focusing on the curation process, the various resources used for curation and the comparison of the SILVA taxonomy with Greengenes and RDP-II taxonomies. Our comparisons not only revealed a reasonable overlap between the taxa names, but also points to significant differences in both names and numbers of taxa between the three resources. © 2013 The Author(s). Published by Oxford University Press.", "date": "2014-01-01T00:00:00Z", "citationCount": 2372, "authors": [ { "name": "Yilmaz P." }, { "name": "Parfrey L.W." }, { "name": "Yarza P." }, { "name": "Gerken J." }, { "name": "Pruesse E." }, { "name": "Quast C." }, { "name": "Schweer T." }, { "name": "Peplies J." }, { "name": "Ludwig W." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/bts252", "pmid": "22556368", "pmcid": "PMC3389763", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes", "abstract": "Motivation: In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements.Results: In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. © The Author(s) 2012. Published by Oxford University Press.", "date": "2012-07-01T00:00:00Z", "citationCount": 2352, "authors": [ { "name": "Pruesse E." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/nar/gks808", "pmid": "22933715", "pmcid": "PMC3592464", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies", "abstract": "16S ribosomal RNA gene (rDNA) amplicon analysis remains the standard approach for the cultivation-independent investigation of microbial diversity. The accuracy of these analyses depends strongly on the choice of primers. The overall coverage and phylum spectrum of 175 primers and 512 primer pairs were evaluated in silico with respect to the SILVA 16S/18S rDNA non-redundant reference dataset (SSURef 108 NR). Based on this evaluation a selection of 'best available' primer pairs for Bacteria and Archaea for three amplicon size classes (100-400, 400-1000, ≥1000 bp) is provided. The most promising bacterial primer pair (S-D-Bact-0341-b-S-17/S-D-Bact-0785-a-A-21), with an amplicon size of 464 bp, was experimentally evaluated by comparing the taxonomic distribution of the 16S rDNA amplicons with 16S rDNA fragments from directly sequenced metagenomes. The results of this study may be used as a guideline for selecting primer pairs with the best overall coverage and phylum spectrum for specific applications, therefore reducing the bias in PCR-based microbial diversity studies. © 2012 The Author(s). Published by Oxford University Press.", "date": "2013-01-01T00:00:00Z", "citationCount": 5992, "authors": [ { "name": "Klindworth A." }, { "name": "Pruesse E." }, { "name": "Schweer T." }, { "name": "Peplies J." }, { "name": "Quast C." }, { "name": "Horn M." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": null, "email": "ngs-contact@arb-silva.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Project", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures", "email": "hub@dsmz.de", "url": "https://www.dsmz.de", "orcidid": null, "gridid": "grid.420081.f", "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "silva", "additionDate": "2016-09-30T07:30:11Z", "lastUpdate": "2025-01-22T09:55:10.038132Z", "editPermission": { "type": "group", "authors": [ "noha_elkayal" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MediaDive", "description": "Comprehensive database on cultivation media and growth conditions for all domains of life. Data derived from culture collections and individuals.", "homepage": "https://mediadive.dsmz.de", "biotoolsID": "mediadive", "biotoolsCURIE": "biotools:mediadive", "version": [], "otherID": [], "relation": [ { "biotoolsID": "bacdive", "type": "uses" }, { "biotoolsID": "mediadive", "type": "includedIn" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_3435", "term": "Standardisation and normalisation" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Data deposition" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2531", "term": "Protocol" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2091", "term": "Accession" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2531", "term": "Protocol" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" }, { "uri": "http://edamontology.org/format_3464", "term": "JSON" }, { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": "Medium Builder", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3786", "term": "Query script" }, "format": [ { "uri": "http://edamontology.org/format_3790", "term": "SPARQL" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_2376", "term": "RDF format" } ] } ], "note": "SPARQL end point", "cmd": null } ], "toolType": [ "Database portal", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" }, { "uri": "http://edamontology.org/topic_3292", "term": "Biochemistry" }, { "uri": "http://edamontology.org/topic_0219", "term": "Data curation and archival" }, { "uri": "http://edamontology.org/topic_3678", "term": "Experimental design and studies" }, { "uri": "http://edamontology.org/topic_0607", "term": "Laboratory information management" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "PHP", "JavaScript" ], "license": "CC-BY-4.0", "collectionID": [ "DSMZ Digital Diversity", "de.NBI" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://mediadive.dsmz.de/docs/website", "type": [ "User manual" ], "note": "General introduction to the web interface" }, { "url": "https://mediadive.dsmz.de/doc/index.html", "type": [ "API documentation" ], "note": null }, { "url": "https://mediadive.dsmz.de/docs/medium-builder", "type": [ "User manual" ], "note": "Medium Builder" } ], "publication": [ { "doi": "10.1093/NAR/GKAC803", "pmid": "36134710", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "MediaDive: the expert-curated cultivation media database", "abstract": "We present MediaDive (https://mediadive.dsmz.de), a comprehensive and expert-curated cultivation media database, which comprises recipes, instructions and molecular compositions of >3200 standardized cultivation media for >40 000 microbial strains from all domains of life. MediaDive is designed to enable broad range applications from every-day-use in research and diagnostic laboratories to knowledge-driven support of new media design and artificial intelligence-driven data mining. It offers a number of intuitive search functions and comparison tools, for example to identify media for related taxonomic groups and to integrate strain-specific modifications. Besides classical PDF archiving and printing, the state-of-the-art website allows paperless use of media recipes on mobile devices for convenient wet-lab use. In addition, data can be retrieved using a RESTful web service for large-scale data analyses. An internal editor interface ensures continuous extension and curation of media by cultivation experts from the Leibniz Institute DSMZ, which is interlinked with the growing microbial collections at DSMZ. External user engagement is covered by a dedicated media builder tool. The standardized and programmatically accessible data will foster new approaches for the design of cultivation media to target the vast majority of uncultured microorganisms.", "date": "2023-01-06T00:00:00Z", "citationCount": 22, "authors": [ { "name": "Koblitz J." }, { "name": "Halama P." }, { "name": "Spring S." }, { "name": "Thiel V." }, { "name": "Baschien C." }, { "name": "Hahnke R.L." }, { "name": "Pester M." }, { "name": "Overmann J." }, { "name": "Reimer L.C." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Julia Koblitz", "email": "julia.koblitz@dsmz.de", "url": "https://research.dsmz.de/person/651cecd8b3c97f11cc28cfc2", "orcidid": "https://orcid.org/0000-0002-7260-2129", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer", "Primary contact", "Developer" ], "note": null }, { "name": "Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH", "email": "hub@dsmz.de", "url": "https://dsmz.de", "orcidid": null, "gridid": null, "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "JKoblitz", "additionDate": "2022-11-09T17:22:40.898557Z", "lastUpdate": "2025-01-22T09:37:58.121773Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" } ] }