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{ "count": 9425, "next": "?page=2", "previous": null, "list": [ { "name": "fermo-core", "description": "fermo-core is the backend of the metabolomics dashboard FERMO. It can be used for large-scale processing of metabolomics data and integration of phenotypic and other orthogonal data.", "homepage": "https://github.com/fermo-metabolomics/fermo_core", "biotoolsID": "fermo-core", "biotoolsCURIE": "biotools:fermo-core", "version": [ "0.6.3" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "MIT", "collectionID": [ "FERMO" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/fermo-metabolomics/fermo_core", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/fermo-metabolomics", "type": [ "Repository" ], "note": "GitHub Community managing FERMO-related repositories" }, { "url": "https://github.com/orgs/fermo-metabolomics/discussions", "type": [ "Discussion forum" ], "note": null } ], "download": [ { "url": "https://github.com/fermo-metabolomics/fermo_core/releases/tag/0.6.3", "type": "Source code", "note": null, "version": "0.6.3" }, { "url": "https://pypi.org/project/fermo-core/0.6.3/", "type": "Source code", "note": "PyPI-deposited wheel and source code", "version": "0.6.3" } ], "documentation": [ { "url": "https://fermo-metabolomics.github.io/fermo_docs/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1101/2022.12.21.521422", "pmid": null, "pmcid": null, "type": [], "version": null, "note": "Preprint released on bioRxiv", "metadata": null } ], "credit": [ { "name": "Mitja M. Zdouc", "email": "zdoucmm@gmail.com", "url": "https://github.com/mmzdouc", "orcidid": "https://orcid.org/0000-0001-6534-6609", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "Lead Developer and Initiator" }, { "name": "Fermo Metabolomics", "email": null, "url": "https://github.com/fermo-metabolomics", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Project", "typeRole": [ "Maintainer" ], "note": "GitHub Community overseeing development of the project" } ], "owner": "mmzdouc", "additionDate": "2025-05-09T18:13:37.471507Z", "lastUpdate": "2025-05-09T18:46:02.403653Z", "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", 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"note": null }, { "url": "https://github.com/paulsengroup/StripePy/discussions", "type": [ "Discussion forum" ], "note": null }, { "url": "https://github.com/paulsengroup/StripePy.git", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/paulsengroup/StripePy/releases", "type": "Source code", "note": null, "version": null }, { "url": "https://hub.docker.com/r/paulsengroup/stripepy", "type": "Container file", "note": null, "version": null }, { "url": "https://doi.org/10.5281/zenodo.14283921", "type": "Test data", "note": null, "version": null }, { "url": "https://pypi.org/project/stripepy-hic/", "type": "Binaries", "note": null, "version": null }, { "url": "https://anaconda.org/bioconda/stripepy-hic", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/paulsengroup/StripePy/blob/main/README.md", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1101/2024.12.20.629789", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "robomics", "additionDate": "2024-12-21T15:24:55.662209Z", "lastUpdate": "2025-05-02T11:01:00.332596Z", "editPermission": { "type": "group", "authors": [ "rea1991" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "OpenSWATH", "description": "OpenSWATH is a proteomics software that allows analysis of LC-MS/MS DIA (data independent acquisition) and implemented as part of OpenMS.", "homepage": "http://www.openswath.org", "biotoolsID": "OpenSWATH", "biotoolsCURIE": "biotools:OpenSWATH", "version": [ "OpenMS 2.4.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0335", "term": "Formatting" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3108", "term": "Experimental measurement" }, "format": [ { "uri": "http://edamontology.org/format_3710", "term": "WIFF format" }, { "uri": "http://edamontology.org/format_3245", "term": "Mass spectrometry data format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3621", "term": "SQLite format" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3215", "term": "Peak detection" }, { "uri": "http://edamontology.org/operation_3628", "term": "Chromatographic alignment" }, { "uri": "http://edamontology.org/operation_3203", "term": "Chromatogram visualisation" }, { "uri": "http://edamontology.org/operation_3649", "term": "Target-Decoy" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3621", "term": "SQLite format" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" } ] }, { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrometry spectra" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" }, { "uri": "http://edamontology.org/format_3246", "term": "TraML" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0944", "term": "Peptide mass fingerprint" }, "format": [ { "uri": "http://edamontology.org/format_3833", "term": "featureXML" }, { "uri": "http://edamontology.org/format_3475", "term": "TSV" }, { "uri": "http://edamontology.org/format_3621", "term": "SQLite format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++" ], "license": "BSD-3-Clause", "collectionID": [ "ms-utils", "Proteomics" ], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/OpenSWATH/docker", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/OpenMS/OpenMS", "type": [ "Repository" ], "note": null }, { "url": "https://sourceforge.net/projects/open-ms/lists/open-ms-general", "type": [ "Mailing list" ], "note": null } ], "download": [ { "url": "http://www.openswath.org/en/latest/docs/binaries.html", "type": "Software package", "note": null, "version": null }, { "url": "http://www.openswath.org/en/latest/docs/sources.html", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://buildmedia.readthedocs.org/media/pdf/openswath/latest/openswath.pdf", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": null, "pmid": "24727770", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data", "abstract": "", "date": "2014-01-01T00:00:00Z", "citationCount": 409, "authors": [ { "name": "Rost H.L." }, { "name": "Rosenberger G." }, { "name": "Navarro P." }, { "name": "Gillet L." }, { "name": "Miladinovia S.M." }, { "name": "Schubert O.T." }, { "name": "Wolski W." }, { "name": "Collins B.C." }, { "name": "Malmstrom J." }, { "name": "Malmstrom L." }, { "name": "Aebersold R." } ], "journal": "Nature Biotechnology" } } ], "credit": [ { "name": "Hannes Röst", "email": "hroest@stanford.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "George Rosenberger", "email": "gr2578@cumc.columbia.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "samwein", "additionDate": "2019-06-18T11:06:01Z", "lastUpdate": "2025-04-30T11:39:29.102190Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "OpenPepXL", "description": "An Open-Source Tool for Sensitive Identification of Cross-Linked Peptides in XL-MS.\n\nProtein-Protein Cross-Linking (OpenPepXL) – OpenMS.\n\nOpenPepXL is a protein-protein cross-link identification tool implemented in C++ as part of OpenMS. It works with all uncleavable labeled and label-free cross-linkers but not (yet) with cleavable ones.", "homepage": "https://openms.org/openpepxl", "biotoolsID": "openpepxl", "biotoolsCURIE": "biotools:openpepxl", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3631", "term": "Peptide identification" }, { "uri": "http://edamontology.org/operation_3629", "term": "Deisotoping" }, { "uri": "http://edamontology.org/operation_3767", "term": "Protein identification" }, { "uri": "http://edamontology.org/operation_3431", "term": "Deposition" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [], "language": [], "license": "BSD-3-Clause", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.openms.de/openpepxl", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1074/MCP.TIR120.002186", "pmid": "33067342", "pmcid": "PMC7710140", "type": [], "version": null, "note": null, "metadata": { "title": "OpenPepXL: An Open-Source Tool for Sensitive Identification of Cross-Linked Peptides in XL-MS", "abstract": "© 2020 Netz et al. Published under exclusive license by The American Society for Biochemistry and Molecular Biology, Inc.Cross-linking MS (XL-MS) has been recognized as an effective source of information about protein structures and interactions. In contrast to regular peptide identification, XL-MS has to deal with a quadratic search space, where peptides from every protein could potentially be cross-linked to any other protein. To cope with this search space, most tools apply different heuristics for search space reduction. We introduce a new open-source XL-MS database search algorithm, OpenPepXL, which offers increased sensitivity compared with other tools. OpenPepXL searches the full search space of an XL-MS experiment without using heuristics to reduce it. Because of efficient data structures and built-in parallelization OpenPepXL achieves excellent runtimes and can also be deployed on large compute clusters and cloud services while maintaining a slim memory footprint. We compared OpenPepXL to several other commonly used tools for identification of noncleavable labeled and label-free cross-linkers on a diverse set of XL-MS experiments. In our first comparison, we used a data set from a fraction of a cell lysate with a protein database of 128 targets and 128 decoys. At 5% FDR, OpenPepXL finds from 7% to over 50% more unique residue pairs (URPs) than other tools. On data sets with available high-resolution structures for cross-link validation OpenPepXL reports from 7% to over 40% more structurally validated URPs than other tools. Additionally, we used a synthetic peptide data set that allows objective validation of cross-links without relying on structural information and found that OpenPepXL reports at least 12% more validated URPs than other tools. It has been built as part of the OpenMS suite of tools and supports Windows, macOS, and Linux operating systems. OpenPepXL also supports the MzIdentML 1.2 format for XL-MS identification results. It is freely available under a three-clause BSD license at https://openms.org/openpepxl.", "date": "2020-12-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Netz E." }, { "name": "Dijkstra T.M.H." }, { "name": "Sachsenberg T." }, { "name": "Zimmermann L." }, { "name": "Walzer M." }, { "name": "Monecke T." }, { "name": "Ficner R." }, { "name": "Dybkov O." }, { "name": "Urlaub H." }, { "name": "Kohlbacher O." } ], "journal": "Molecular and Cellular Proteomics" } } ], "credit": [ { "name": "Eugen Netz", "email": "eugen.netz@tuebingen.mpg.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Oliver Kohlbacher", "email": "oliver.kohlbacher@uni-tuebingen.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "samwein", "additionDate": "2021-01-18T11:10:26Z", "lastUpdate": "2025-04-30T11:39:28.349250Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "sylph", "description": "fast and precise species-level metagenomic profiling with ANIs", "homepage": "https://github.com/bluenote-1577/sylph", "biotoolsID": "sylph", "biotoolsCURIE": "biotools:sylph", "version": [ "v0.4.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3751", "term": "DSV" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" } ], "operatingSystem": [ "Linux" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "pauffret", "additionDate": "2023-12-06T15:45:20.587393Z", "lastUpdate": "2025-04-24T09:31:08.371089Z", "editPermission": { "type": "group", "authors": [ "vashokan" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "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": "Bracken", "description": "Statistical method that computes the abundance of species in DNA sequences from a metagenomics sample.", "homepage": "https://ccb.jhu.edu/software/bracken/", "biotoolsID": "bracken", "biotoolsCURIE": "biotools:bracken", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" } ], "operatingSystem": [ "Linux" ], "language": [ "Perl", "Python" ], "license": "GPL-3.0", "collectionID": [ "Animal and Crop Genomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/jenniferlu717/Bracken", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/jenniferlu717/Bracken/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://ccb.jhu.edu/software/bracken/index.shtml?t=manual", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.7717/peerj-cs.104", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Bracken: Estimating species abundance in metagenomics data", "abstract": "Metagenomic experiments attempt to characterize microbial communities using high-throughput DNA sequencing. Identification of the microorganisms in a sample provides information about the genetic profile, population structure, and role of microorganisms within an environment. Until recently, most metagenomics studies focused on high-level characterization at the level of phyla, or alternatively sequenced the 16S ribosomalRNAgene that is present in bacterial species. As the cost of sequencing has fallen, though, metagenomics experiments have increasingly used unbiased shotgun sequencing to capture all the organisms in a sample. This approach requires a method for estimating abundance directly from the raw read data. Here we describe a fast, accurate new method that computes the abundance at the species level using the reads collected in a metagenomics experiment. Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN) uses the taxonomic assignments made by Kraken, a very fast read-level classifier, along with information about the genomes themselves to estimate abundance at the species level, the genus level, or above. We demonstrate that Bracken can produce accurate species- and genus-level abundance estimates even when a sample contains multiple near-identical species.", "date": "2017-01-01T00:00:00Z", "citationCount": 900, "authors": [ { "name": "Lu J." }, { "name": "Breitwieser F.P." }, { "name": "Thielen P." }, { "name": "Salzberg S.L." } ], "journal": "PeerJ Computer Science" } } ], "credit": [ { "name": null, "email": "jlu26@jhmi.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "admin", "additionDate": "2017-08-20T15:17:20Z", "lastUpdate": "2025-04-23T07:43:18.805990Z", "editPermission": { "type": "group", "authors": [ "animalandcropgenomics", "ELIXIR-CZ", "bebatut", "vashokan" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MetaPhlAn", "description": "Computational tool for profiling the composition of microbial communities from metagenomic shotgun sequencing data.", "homepage": "http://segatalab.cibio.unitn.it/tools/metaphlan/index.html", "biotoolsID": "metaphlan", "biotoolsCURIE": "biotools:metaphlan", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" }, { "uri": "http://edamontology.org/format_1929", "term": "FASTA" }, { "uri": "http://edamontology.org/format_2573", "term": "SAM" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3751", "term": "DSV" } ] } ], "note": null, "cmd": "metaphlan <fastq_input> --input_type fastq -o <output>" }, { "operation": [ { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3751", "term": "DSV" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3751", "term": "DSV" } ] } ], "note": "Convert SGB-based profile to GTDB taxonomy", "cmd": "sgb_to_gtdb_profile.py -i <metaphlan_output> -o <gtdb_metaphlan_output>" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_0194", "term": "Phylogenomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "MIT", "collectionID": [ "Animal and Crop Genomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/biobakery/MetaPhlAn", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/nmeth.2066", "pmid": "22688413", "pmcid": "PMC3443552", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Metagenomic microbial community profiling using unique clade-specific marker genes", "abstract": "Metagenomic shotgun sequencing data can identify microbes populating a microbial community and their proportions, but existing taxonomic profiling methods are inefficient for increasingly large data sets. We present an approach that uses clade-specific marker genes to unambiguously assign reads to microbial clades more accurately and >50Ã-faster than current approaches. We validated our metagenomic phylogenetic analysis tool, MetaPhlAn, on terabases of short reads and provide the largest metagenomic profiling to date of the human gut. It can be accessed at http://huttenhower.sph.harvard.edu/ metaphlan/. © 2012 Nature America, Inc. All rights reserved.", "date": "2012-08-01T00:00:00Z", "citationCount": 1300, "authors": [ { "name": "Segata N." }, { "name": "Waldron L." }, { "name": "Ballarini A." }, { "name": "Narasimhan V." }, { "name": "Jousson O." }, { "name": "Huttenhower C." } ], "journal": "Nature Methods" } } ], "credit": [ { "name": null, "email": null, "url": "https://groups.google.com/forum/#!forum/metaphlan-users", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "admin", "additionDate": "2017-08-20T15:57:59Z", "lastUpdate": "2025-04-22T12:44:24.859435Z", "editPermission": { "type": "group", "authors": [ "animalandcropgenomics", "ELIXIR-CZ", "bebatut", "vashokan" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "samclip", "description": "Filter SAM file for soft and hard clipped alignments", "homepage": "https://github.com/tseemann/samclip", "biotoolsID": "samclip", "biotoolsCURIE": "biotools:samclip", "version": [ "0.4.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3192", "term": "Sequence trimming" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0102", "term": "Mapping" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Perl" ], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/tseemann/samclip", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://anaconda.org/bioconda/samclip", "type": "Software package", "note": null, "version": "0.4.0" } ], "documentation": [ { "url": "https://github.com/tseemann/samclip", "type": [ "General" ], "note": null } ], "publication": [], "credit": [], "owner": "emmcauley", "additionDate": "2025-04-21T21:06:51.624399Z", "lastUpdate": "2025-04-21T21:06:51.626575Z", "editPermission": { "type": "group", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "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": "DICOM tags extractor", "description": "The tool scans the imaging DICOM files of a defined directory at the series level, and produces as output one single JSON file containing all the DICOM tags for each detected series.\nIf a list of selected DICOM tags is provided, the tool can also produce one single csv file containing the listed DICOM tags.\nTo use this tool, the user can download an executable file (.exe). Two execution modes are available : manual execution and command line execution.\nFor the tool to scan data successfully, it is important that : 1/ the extension “.dcm” is visible, as the tool only scans those files, and discard any other; 2/ each DICOM series has its own folder, as the tool gets a single .dcm file from each folder and extracts the tags.", "homepage": "https://www.bcplatforms.com/", "biotoolsID": "dicom_tags_extractor", "biotoolsCURIE": "biotools:dicom_tags_extractor", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0335", "term": "Data formatting" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3365", "term": "Data architecture, analysis and design" }, { "uri": "http://edamontology.org/topic_3384", "term": "Medical imaging" } ], "operatingSystem": [], "language": [], "license": "Not licensed", "collectionID": [ "EUCAIM" ], "maturity": "Emerging", "cost": "Free of charge (with restrictions)", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.bcplatforms.com/", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [], "publication": [], "credit": [ { "name": "BC|Platforms", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "lsaint-aubert", "additionDate": "2025-04-18T15:04:18.411979Z", "lastUpdate": "2025-04-18T15:15:06.042639Z", "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": "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": "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": "ChemFH", "description": "An integrated online platform developed for the screening and prediction of potential frequent drug hitters, thus improving the efficiency of drug R&D in colloidal aggregate, firefly luciferase reporter enzyme inhibition, fluorescence, chemical reactivity, and promiscuity. ChemFH: an integrated tool for screening frequent false positives in chemical biology and drug discovery.", "homepage": "https://chemfh.scbdd.com/", "biotoolsID": "chemfh", "biotoolsCURIE": "biotools:chemfh", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3938", "term": "Virtual screening" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2301", "term": "SMILES string" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1696", "term": "Drug report" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1712", "term": "Chemical structure image" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Script", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0209", "term": "Medicinal chemistry" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "JavaScript" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/antwiser/ChemFH", "type": [ "Repository" ], "note": null }, { "url": "https://chemfh.scbdd.com/", "type": [ "Other" ], "note": "Webpage of the tool" } ], "download": [ { "url": "https://github.com/antwiser/ChemFH/releases/tag/ChemFH-1.0.0", "type": "Source code", "note": null, "version": "1.0.0" } ], "documentation": [ { "url": "https://github.com/antwiser/ChemFH/blob/main/README.md", "type": [ "General" ], "note": null }, { "url": "https://chemfh.scbdd.com/documentation/#/", "type": [ "Quick start guide" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkae424", "pmid": "38783035", "pmcid": "PMC11223804", "type": [ "Method" ], "version": "1.0.0", "note": "High-throughput screening rapidly tests an extensive array of chemical compounds to identify hit compounds for specific biological targets in drug discovery. However, false-positive results disrupt hit compound screening, leading to wastage of time and resources. To address this, we propose ChemFH, an integrated online platform facilitating rapid virtual evaluation of potential false positives, including colloidal aggregators, spectroscopic interference compounds, firefly luciferase inhibitors, chemical reactive compounds, promiscuous compounds, and other assay interferences. ChemFH is freely available via https://chemfh.scbdd.com/.", "metadata": { "title": "ChemFH: An integrated tool for screening frequent false positives in chemical biology and drug discovery", "abstract": "High-throughput screening rapidly tests an extensive array of chemical compounds to identify hit compounds for specific biological targets in drug discovery. However, false-positive results disrupt hit compound screening, leading to wastage of time and resources. To address this, we propose ChemFH, an integrated online platform facilitating rapid virtual evaluation of potential false positives, including colloidal aggregators, spectroscopic interference compounds, firefly luciferase inhibitors, chemical reactive compounds, promiscuous compounds, and other assay interferences. By leveraging a dataset containing 823 391 compounds, we constructed high-quality prediction models using multi-task directed message-passing network (DMPNN) architectures combining uncertainty estimation, yielding an average AUC value of 0.91. Furthermore, ChemFH incorporated 1441 representative alert substructures derived from the collected data and ten commonly used frequent hitter screening rules. ChemFH was validated with an external set of 75 compounds. Subsequently, the virtual screening capability of ChemFH was successfully confirmed through its application to five virtual screening libraries. Furthermore, ChemFH underwent additional validation on two natural products and FDA-approved drugs, yielding reliable and accurate results. ChemFH is a comprehensive, reliable, and computationally efficient screening pipeline that facilitates the identification of true positive results in assays, contributing to enhanced efficiency and success rates in drug discovery. ChemFH is freely available via https://chemfh.scbdd.com/.", "date": "2024-07-05T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Shi S." }, { "name": "Fu L." }, { "name": "Yi J." }, { "name": "Yang Z." }, { "name": "Zhang X." }, { "name": "Deng Y." }, { "name": "Wang W." }, { "name": "Wu C." }, { "name": "Zhao W." }, { "name": "Hou T." }, { "name": "Zeng X." }, { "name": "Lyu A." }, { "name": "Cao D." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Jiacai Yi", "email": "yjc@nudt.edu.cn", "url": "https://github.com/antwiser", "orcidid": "https://orcid.org/0000-0001-6823-1882", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "National University of Defense Technology, Changsha, Hunan" } ], "owner": "etepf22", "additionDate": "2025-03-28T11:01:52.929561Z", "lastUpdate": "2025-03-28T12:04:07.529430Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, 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[ { "uri": "http://edamontology.org/format_3620", "term": "xlsx" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": "./prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y config.yaml -w NameOfAnalysis -s DIANN\n# and again you run the version within the docker container with\n# ./prolfquapp_docker.sh prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y config.yaml -w NameOfAnalysis -s DIANN" }, { "operation": [ { "uri": "http://edamontology.org/operation_2428", "term": "Validation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_3620", "term": "xlsx" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3914", "term": "Quality control report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0571", 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differential expression analysis (DEA) of proteins. As experiments grow in complexity, involving more samples, groups, and identified proteins, interactive differential expression analysis tools become impractical. The prolfquapp addresses this challenge by providing a command-line interface that simplifies DEA, making it accessible to nonprogrammers and seamlessly integrating it into workflow management systems. Prolfquapp streamlines data processing and result visualization by generating dynamic HTML reports that facilitate the exploration of differential expression results. These reports allow for investigating complex experiments, such as those involving repeated measurements or multiple explanatory variables. Additionally, prolfquapp supports various output formats, including XLSX files, SummarizedExperiment objects and rank files, for further interactive analysis using spreadsheet software, the exploreDE Shiny application, or gene set enrichment analysis software, respectively. By leveraging advanced statistical models from the prolfqua R package, prolfquapp offers a user-friendly, integrated solution for large-scale quantitative proteomics studies, combining efficient data processing with insightful, publication-ready outputs.", "date": "2025-02-07T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Wolski W.E." }, { "name": "Grossmann J." }, { "name": "Schwarz L." }, { "name": "Leary P." }, { "name": "Turker C." }, { "name": "Nanni P." }, { "name": "Schlapbach R." }, { "name": "Panse C." } ], "journal": "Journal of Proteome Research" } } ], "credit": [], "owner": "n.m.palmblad@lumc.nl", "additionDate": "2025-02-28T15:04:33.594183Z", "lastUpdate": "2025-03-28T10:18:25.715685Z", "editPermission": { "type": "group", "authors": [ "thatmariia" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "rocrate-validator", "description": "rocrate-validator is a tool and Python package to validate RO-Crates against different profiles, including the base RO-Crate profile and various extensions.", "homepage": "https://rocrate-validator.readthedocs.io/", "biotoolsID": "rocrate-validator", "biotoolsCURIE": "biotools:rocrate-validator", "version": [], "otherID": [], "relation": [ { "biotoolsID": "lifemonitor", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0336", "term": "Format validation" } ], "input": [], "output": [], "note": "Validate compliance of RO-Crate objects with specifications", "cmd": "`rocrate-validator validate <path_to_rocrate>`" } ], "toolType": [ "Command-line tool", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3572", "term": "Data quality management" }, { "uri": "http://edamontology.org/topic_4012", "term": "FAIR data" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" }, { "uri": "http://edamontology.org/topic_3071", "term": "Data management" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/crs4/rocrate-validator", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/crs4/rocrate-validator/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/crs4/rocrate-validator/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://pypi.org/project/roc-validator/#files", "type": "Downloads page", "note": null, "version": null } ], "documentation": [ { "url": "https://rocrate-validator.readthedocs.io/", "type": [ "API documentation", "Command-line options", "Installation instructions", "Quick start guide" ], "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": [ "Maintainer", "Primary contact", "Developer" ], "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 } ], "owner": "mep", "additionDate": "2025-03-25T09:59:44.309666Z", "lastUpdate": "2025-03-25T12:19:18.196376Z", "editPermission": { "type": "group", "authors": [ "mep", "ilveroluca" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DeepAnnotation", "description": "The python package 'DeepAnnotation' can be used to perform genomic selection (GS), which is a promising breeding strategy for agricultural breeding. 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Spacedust adapts the fast and sensitive structure comparisons of Foldseek and homology search capabilities of MMseqs2. It introduces a novel approach of aggregating sets of homologous hits between pairs of genomes and identifies cluster of hits with conserved gene neighborhood between each using agglomerative hierarchical clustering algorithm.", "homepage": "https://github.com/soedinglab/spacedust/", "biotoolsID": "spacedust", "biotoolsCURIE": "biotools:spacedust", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "C++" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1101/2024.10.02.616292v1", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "milot-mirdita", "additionDate": "2025-03-20T09:46:51.356874Z", "lastUpdate": "2025-03-20T09:46:51.359476Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "chewBBaca", "description": "chewBBACA is a software suite for the creation and evaluation of core genome and whole genome MultiLocus Sequence Typing (cg/wgMLST) schemas and results.", "homepage": "https://github.com/B-UMMI/chewBBACA", "biotoolsID": "chewbbaca", "biotoolsCURIE": "biotools:chewbbaca", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3840", "term": "Multilocus sequence typing" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://chewbbaca.readthedocs.io/en/latest/index.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1099/MGEN.0.000166", "pmid": "29543149", "pmcid": "PMC5885018", "type": [], "version": null, "note": null, "metadata": { "title": "chewBBACA: A complete suite for gene-by-gene schema creation and strain identification", "abstract": "Gene-by-gene approaches are becoming increasingly popular in bacterial genomic epidemiology and outbreak detection. However, there is a lack of open-source scalable software for schema definition and allele calling for these methodologies. The chewBBACA suite was designed to assist users in the creation and evaluation of novel whole-genome or core-genome gene-by-gene typing schemas and subsequent allele calling in bacterial strains of interest. chewBBACA performs the schema creation and allele calls on complete or draft genomes resulting from de novo assemblers. The chewBBACA software uses Python 3.4 or higher and can run on a laptop or in high performance clusters making it useful for both small laboratories and large reference centers. ChewBBACA is available at https://github.com/B-UMMI/chewBBACA.", "date": "2018-03-01T00:00:00Z", "citationCount": 276, "authors": [ { "name": "Silva M." }, { "name": "Machado M.P." }, { "name": "Silva D.N." }, { "name": "Rossi M." }, { "name": "Moran-Gilad J." }, { "name": "Santos S." }, { "name": "Ramirez M." }, { "name": "Carrico J.A." } ], "journal": "Microbial genomics" } } ], "credit": [], "owner": "EngyNasr", "additionDate": "2025-03-17T15:56:34.552871Z", "lastUpdate": "2025-03-19T14:47:22.843193Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "pyMLST", "description": "A Python Mlst Local Search Tool. The input can be (i) an assembler-generated draft genome, (ii) the direct raw data, or (iii) other genomes stored in the sequence database.", "homepage": "https://github.com/bvalot/pyMLST", "biotoolsID": "pymlst", "biotoolsCURIE": "biotools:pymlst", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3840", "term": "Multilocus sequence typing" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" } ], "operatingSystem": [], "language": [ "Python" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://pymlst.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1099/mgen.0.001126", "pmid": "37966168", "pmcid": "PMC10711306", "type": [], "version": null, "note": null, "metadata": { "title": "Introduction and benchmarking of pyMLST: open-source software for assessing bacterial clonality using core genome MLST", "abstract": "Core genome multilocus sequence typing (cgMLST) has gained in popularity for bacterial typing since whole-genome sequencing (WGS) has become affordable. We introduce here pyMLST, a new complete, stand-alone, free and open source pipeline for cgMLST analysis. pyMLST can create or import a core genome database. For each gene, the first allele is aligned against the bacterial genome of interest using BLAT. Incomplete genes are aligned using MAFT. All data are stored in a SQLite database. pyMLST accepts assembly genomes or raw data (with the option pyMLST-KMA) as input. To evaluate our new tool, we selected three genome collections of major bacterial pathogens (Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus) and compared them with pyMLST, pyMLST-KMA, ChewBBACA, SeqSphere and the variant calling approach. We compared the sensitivity, precision and false-positive rate for each method with those of the variant calling approach. Minimal spanning trees were generated with each type of software to evaluate their interest in the context of a bacterial outbreak. We found that pyMLST-KMA is a convenient screening method to avoid assembling large bacterial collections. 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"Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_3375", "term": "Drug metabolism" }, { "uri": "http://edamontology.org/topic_3370", "term": "Analytical chemistry" } ], "operatingSystem": [], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/agnesbrnb/MetIDfyR", "type": [ "Quick start guide", "Installation instructions", "Citation instructions" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.analchem.0c02281", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "MetIDfyR: An Open-Source R Package to Decipher Small-Molecule Drug Metabolism through High-Resolution Mass Spectrometry", "abstract": "With recent advances in analytical chemistry, liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS) has become an essential tool for metabolite discovery and detection. Even if most of the common drug transformations have already been extensively described, manual search of drug metabolites in LC-HRMS/MS datasets is still a common practice in toxicology laboratories, complicating metabolite discovery. Furthermore, the availability of free open-source software for metabolite discovery is still limited. In this article, we present MetIDfyR, an open-source and cross-platform R package for in silico drug phase I/II biotransformation prediction and mass-spectrometric data mining. MetIDfyR has proven its efficacy for advanced metabolite identification in semi-complex and complex mixtures in in vitro or in vivo drug studies and is freely available at github.com/agnesblch/MetIDfyR.", "date": "2020-10-06T00:00:00Z", "citationCount": 10, "authors": [ { "name": "Delcourt V." }, { "name": "Barnabe A." }, { "name": "Loup B." }, { "name": "Garcia P." }, { "name": "Andre F." }, { "name": "Chabot B." }, { "name": "Trevisiol S." }, { "name": "Moulard Y." }, { "name": "Popot M.-A." }, { "name": "Bailly-Chouriberry L." } ], "journal": "Analytical Chemistry" } } ], "credit": [], "owner": "agnesbarnabe", "additionDate": "2021-01-18T09:08:27Z", "lastUpdate": "2025-02-27T15:46:01.807140Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "COPASI", "description": "Open-source software application for creating and solving mathematical models of biological processes such as metabolic networks, cell-signaling pathways, regulatory networks, infectious diseases, and many others. It includes features to define models of biological processes, simulate and analyze these models, generate analysis reports, and import/export models in SBML format.", "homepage": "http://copasi.org/", "biotoolsID": "copasi", "biotoolsCURIE": "biotools:copasi", "version": [], "otherID": [], "relation": [ { "biotoolsID": "corc", "type": "usedBy" }, { "biotoolsID": "pycotools", "type": "usedBy" }, { "biotoolsID": "biosimulations", "type": "includedIn" }, { "biotoolsID": "sbmlwebapp", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3562", "term": "Network simulation" }, { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" }, { "uri": "http://edamontology.org/operation_3660", "term": "Metabolic network modelling" }, { "uri": "http://edamontology.org/operation_3926", "term": "Pathway visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2600", "term": "Pathway or network" }, "format": [ { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_3239", "term": "CopasiML" }, { "uri": "http://edamontology.org/format_3685", "term": "SED-ML" }, { "uri": "http://edamontology.org/format_3686", "term": "COMBINE OMEX" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2600", "term": "Pathway or network" }, "format": [ { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_3239", "term": "CopasiML" }, { "uri": "http://edamontology.org/format_3685", "term": "SED-ML" }, { "uri": "http://edamontology.org/format_3686", "term": "COMBINE OMEX" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++" ], "license": "Artistic-2.0", "collectionID": [ "de.NBI", "EBI Training Tools" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://groups.google.com/g/copasi-user-forum", "type": [ "Discussion forum" ], "note": "User Forum" }, { "url": "http://tracker.copasi.org/", "type": [ "Issue tracker" ], "note": "Issue tracker" }, { "url": "https://github.com/copasi/COPASI", "type": [ "Repository" ], "note": "Github Repo" }, { "url": "https://fosstodon.org/@copasi", "type": [ "Social media" ], "note": null } ], "download": [ { "url": "http://copasi.org/Download/", "type": "Binaries", "note": "Source and binary packages are available for download.", "version": null } ], "documentation": [ { "url": "http://copasi.org/Support/User_Manual/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btl485", "pmid": "17032683", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "COPASI - A COmplex PAthway SImulator", "abstract": "Motivation: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods. Results: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic-stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation. © 2006 Oxford University Press.", "date": "2006-12-15T00:00:00Z", "citationCount": 1960, "authors": [ { "name": "Hoops S." }, { "name": "Gauges R." }, { "name": "Lee C." }, { "name": "Pahle J." }, { "name": "Simus N." }, { "name": "Singhal M." }, { "name": "Xu L." }, { "name": "Mendes P." }, { "name": "Kummer U." } ], "journal": "Bioinformatics" } }, { "doi": "10.1007/978-1-59745-525-1_2", "pmid": "19399433", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Computational modeling of biochemical networks using COPASI", "abstract": "Computational modeling and simulation of biochemical networks is at the core of systems biology and this includes many types of analyses that can aid understanding of how these systems work. COPASI is a generic software package for modeling and simulation of biochemical networks which provides many of these analyses in convenient ways that do not require the user to program or to have deep knowledge of the numerical algorithms. Here we provide a description of how these modeling techniques can be applied to biochemical models using COPASI. The focus is both on practical aspects of software usage as well as on the utility of these analyses in aiding biological understanding. Practical examples are described for steady-state and time-course simulations, stoichiometric analyses, parameter scanning, sensitivity analysis (including metabolic control analysis), global optimization, parameter estimation, and stochastic simulation. The examples used are all published models that are available in the BioModels database in SBML format. © 2009 Humana Press.", "date": "2009-12-01T00:00:00Z", "citationCount": 168, "authors": [ { "name": "Mendes P." }, { "name": "Hoops S." }, { "name": "Sahle S." }, { "name": "Gauges R." }, { "name": "Dada J." }, { "name": "Kummer U." } ], "journal": "Methods in Molecular Biology" } }, { "doi": "10.1016/j.jbiotec.2017.06.1200", "pmid": "28655634", "pmcid": "PMC5623632", "type": [], "version": null, "note": null, "metadata": { "title": "COPASI and its applications in biotechnology", "abstract": "COPASI is software used for the creation, modification, simulation and computational analysis of kinetic models in various fields. It is open-source, available for all major platforms and provides a user-friendly graphical user interface, but is also controllable via the command line and scripting languages. These are likely reasons for its wide acceptance. We begin this review with a short introduction describing the general approaches and techniques used in computational modeling in the biosciences. Next we introduce the COPASI package, and its capabilities, before looking at typical applications of COPASI in biotechnology.", "date": "2017-11-10T00:00:00Z", "citationCount": 75, "authors": [ { "name": "Bergmann F.T." }, { "name": "Hoops S." }, { "name": "Klahn B." }, { "name": "Kummer U." }, { "name": "Mendes P." }, { "name": "Pahle J." }, { "name": "Sahle S." } ], "journal": "Journal of Biotechnology" } } ], "credit": [ { "name": null, "email": null, "url": "http://copasi.org/About/Team/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Frank T. 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" ], "note": null } ], "owner": "frankbergmann", "additionDate": "2017-01-17T15:07:47Z", "lastUpdate": "2025-02-26T13:59:11.356816Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MAGNETO", "description": "An automated workflow for genome-resolved metagenomics", "homepage": "https://gitlab.univ-nantes.fr/bird_pipeline_registry/magneto", "biotoolsID": "magneto", "biotoolsCURIE": "biotools:magneto", "version": [ "1.2" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0310", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/operation_3192", "term": "Sequence trimming" }, { "uri": "http://edamontology.org/operation_3219", "term": "Read pre-processing" }, { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" }, { "uri": "http://edamontology.org/operation_2454", "term": "Gene prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" }, { "uri": "http://edamontology.org/format_3989", "term": "GZIP format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1872", "term": "Taxonomic classification" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_0916", "term": "Gene report" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] } ], "note": null, "cmd": "magneto run all --profile config/slurm/ --config target=single_assembly --rerun-incomplete" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" }, { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" }, { "uri": "http://edamontology.org/topic_3050", "term": "Biodiversity" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://gitlab.univ-nantes.fr/bird_pipeline_registry/magneto", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://gitlab.univ-nantes.fr/bird_pipeline_registry/magneto/-/releases/1.2", "type": "Source code", "note": null, "version": "1.2" }, { "url": "https://anaconda.org/bioconda/magneto", "type": "Software package", "note": null, "version": "1.2" } ], "documentation": [ { "url": "https://gitlab.univ-nantes.fr/bird_pipeline_registry/magneto/-/wikis/home", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1128/msystems.00432-22", "pmid": "35703559", "pmcid": "PMC9426564", "type": [], "version": null, "note": null, "metadata": { "title": "MAGNETO: An Automated Workflow for Genome-Resolved Metagenomics", "abstract": "Metagenome-assembled genomes (MAGs) represent individual genomes recovered from metagenomic data. MAGs are extremely useful to analyze uncultured microbial genomic diversity, as well as to characterize associated functional and metabolic potential in natural environments. Recent computational developments have considerably improved MAG reconstruction but also emphasized several limitations, such as the nonbinning of sequence regions with repetitions or distinct nucleotidic composition. Different assembly and binning strategies are often used; however, it still remains unclear which assembly strategy, in combination with which binning approach, offers the best performance for MAG recovery. Several workflows have been proposed in order to reconstruct MAGs, but users are usually limited to single-metagenome assembly or need to manually define sets of metagenomes to coassemble prior to genome binning. Here, we present MAGNETO, an automated workflow dedicated to MAG reconstruction, which includes a fully-automated coassembly step informed by optimal clustering of metagenomic distances, and implements complementary genome binning strategies, for improving MAG recovery. MAGNETO is implemented as a Snakemake workflow and is available at: https://gitlab.univ-nantes.fr/bird_pipeline_registry/magneto. IMPORTANCE Genome-resolved metagenomics has led to the discovery of previously untapped biodiversity within the microbial world. As the development of computational methods for the recovery of genomes from metagenomes continues, existing strategies need to be evaluated and compared to eventually lead to standardized computational workflows. In this study, we compared commonly used assembly and binning strategies and assessed their performance using both simulated and real metagenomic data sets. We propose a novel approach to automate coassembly, avoiding the requirement for a priori knowledge to combine metagenomic information. The comparison against a previous coassembly approach demonstrates a strong impact of this step on genome binning results, but also the benefits of informing coassembly for improving the quality of recovered genomes. MAGNETO integrates complementary assembly-binning strategies to optimize genome reconstruction and provides a complete reads-to-genomes workflow for the growing microbiome research community.", "date": "2022-08-01T00:00:00Z", "citationCount": 8, "authors": [ { "name": "Churcheward B." }, { "name": "Millet M." }, { "name": "Bihouee A." }, { "name": "Fertin G." }, { "name": "Chaffron S." } ], "journal": "mSystems" } } ], "credit": [ { "name": "Samuel Chaffron", "email": "samuel.chaffron@ls2n.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Benjamin Churcheward", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Audrey Bihouée", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { 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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": "SqueezeCall", "description": "SqueezeCall: Nanopore basecalling using a Squeezeformer network.\n\nIn SqueezeCall, convolution layers are used to downsample raw signals. A Squeezeformer network is employed to capture global context. Finally, a CTC decoder generates the DNA sequence by a beam search algorithm. Experiments on multiple species further demonstrate the potential of the Squeezeformer-based model to improve basecalling accuracy and its superiority over a recurrent neural network (RNN)-based model and Transformer-based models.", "homepage": "https://github.com/labcbb/SqueezeCall", "biotoolsID": "squeezecall", "biotoolsCURIE": "biotools:squeezecall", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3185", "term": "Base-calling" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [], "language": [], "license": "MIT", "collectionID": [], "maturity": null, "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/labcbb/SqueezeCall", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/labcbb/SqueezeCall", "type": "Downloads page", "note": null, "version": null } ], "documentation": [], "publication": [], "credit": [], "owner": "zhongxu", "additionDate": "2025-01-21T07:17:21.626185Z", "lastUpdate": "2025-01-21T07:21:03.653555Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PHIStruct", "description": "PHIStruct is a phage-host interaction prediction tool that uses structure-aware protein embeddings to represent the receptor-binding proteins (RBPs) of phages. \n\nBy incorporating structure information, it presents improvements over using sequence-only protein embeddings and feature-engineered sequence properties — especially for phages with RBPs that have low sequence similarity to those of known phages.", "homepage": "https://github.com/bioinfodlsu/PHIStruct", "biotoolsID": "phistruct", "biotoolsCURIE": "biotools:phistruct", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2423", "term": "Prediction and recognition" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": "Predicts the host genus of a phage given its receptor-binding protein sequences", "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0781", "term": "Virology" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/bioinfodlsu/PHIStruct", "type": [ "Repository" ], "note": null }, { "url": "http://phistruct.bioinfodlsu.com/", "type": [ "Service" ], "note": null } ], "download": [ { "url": "https://github.com/bioinfodlsu/PHIStruct", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/bioinfodlsu/PHIStruct", "type": [ "Installation instructions", "Quick start guide", "Citation instructions", "Command-line options" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btaf016", "pmid": "39804673", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Mark Edward M. Gonzales", "email": "gonzales.markedward@gmail.com", "url": "https://github.com/memgonzales", "orcidid": "https://orcid.org/0000-0001-5050-3157", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "Research Assistant, Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, De La Salle University, Manila, Philippines" }, { "name": "Jennifer C. Ureta", "email": "jennifer.ureta@gmail.com", "url": "https://scholar.google.com/citations?user=v0Tf_u4AAAAJ&hl=en", "orcidid": "https://orcid.org/0000-0003-0427-5311", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Faculty, Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, De La Salle University, Manila, Philippines" }, { "name": "Anish M.S. Shrestha", "email": "anish.shrestha@dlsu.edu.ph", "url": "https://a-transposable-element.com/", "orcidid": "https://orcid.org/0000-0002-9192-9709", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "Head, Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, De La Salle University, Manila, Philippines" } ], "owner": "memgonzales", "additionDate": "2025-01-14T09:14:56.273060Z", "lastUpdate": "2025-01-14T09:14:56.275331Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PHIEmbed", "description": "PHIEmbed is a phage-host interaction prediction tool that uses protein language models to represent the receptor-binding proteins of phages. It presents improvements over using handcrafted (manually feature-engineered) sequence properties and eliminates the need to manually extract and select features from phage sequences.", "homepage": "https://github.com/bioinfodlsu/phage-host-prediction", "biotoolsID": "phiembed", "biotoolsCURIE": "biotools:phiembed", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2423", "term": "Prediction and recognition" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": "Predicts the host genus of a phage given its receptor-binding protein sequences", "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0781", "term": "Virology" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/bioinfodlsu/phage-host-prediction", "type": [ "Repository" ], "note": null }, { "url": "http://phiembed.bioinfodlsu.com/", "type": [ "Service" ], "note": null } ], "download": [ { "url": "https://github.com/bioinfodlsu/phage-host-prediction", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/bioinfodlsu/phage-host-prediction", "type": [ "Installation instructions", "Quick start guide", "Citation instructions", "Command-line options" ], "note": null } ], "publication": [ { "doi": "10.1371/journal.pone.0289030", "pmid": "37486915", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Protein embeddings improve phage-host interaction prediction", "abstract": "With the growing interest in using phages to combat antimicrobial resistance, computational methods for predicting phage-host interactions have been explored to help shortlist candidate phages. Most existing models consider entire proteomes and rely on manual feature engineering, which poses difficulty in selecting the most informative sequence properties to serve as input to the model. In this paper, we framed phage-host interaction prediction as a multiclass classification problem that takes as input the embeddings of a phage’s receptor-binding proteins, which are known to be the key machinery for host recognition, and predicts the host genus. We explored different protein language models to automatically encode these protein sequences into dense embeddings without the need for additional alignment or structural information. We show that the use of embeddings of receptor-binding proteins presents improvements over handcrafted genomic and protein sequence features. The highest performance was obtained using the transformer-based protein language model ProtT5, resulting in a 3% to 4% increase in weighted F1 and recall scores across different prediction confidence thresholds, compared to using selected handcrafted sequence features.", "date": "2023-07-01T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Gonzales M.E.M." }, { "name": "Ureta J.C." }, { "name": "Shrestha A.M.S." } ], "journal": "PLoS ONE" } } ], "credit": [ { "name": "Mark Edward M. Gonzales", "email": "gonzales.markedward@gmail.com", "url": "https://github.com/memgonzales", "orcidid": "https://orcid.org/0000-0001-5050-3157", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": "Research Assistant, Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, De La Salle University, Manila, Philippines" }, { "name": "Jennifer C. Ureta", "email": "jennifer.ureta@gmail.com", "url": "https://scholar.google.com/citations?user=v0Tf_u4AAAAJ&hl=en", "orcidid": "https://orcid.org/0000-0003-0427-5311", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": "Faculty, Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, De La Salle University, Manila, Philippines" }, { "name": "Anish M.S. Shrestha", "email": "anish.shrestha@dlsu.edu.ph", "url": "https://a-transposable-element.com/", "orcidid": "https://orcid.org/0000-0002-9192-9709", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "Head, Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, De La Salle University, Manila, Philippines" } ], "owner": "memgonzales", "additionDate": "2024-05-05T10:53:14.688391Z", "lastUpdate": "2025-01-14T09:13:55.932761Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DiffCorr", "description": "An R package to analyze and visualize differential correlations in biological networks. This package can explore differential correlations between 2 conditions in the context of post-genomics data types, namely transcriptomics and metabolomics. DiffCorr is simple to use in calculating differential correlations and is suitable for the first step towards inferring causal relationships and detecting biomarker candidates.", "homepage": "https://CRAN.R-project.org/package=DiffCorr", "biotoolsID": "diffcorr", "biotoolsCURIE": "biotools:diffcorr", "version": [ "0.4.4" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3391", "term": "Omics" }, { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_3518", "term": "Microarray experiment" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/afukushima/DiffCorr", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://cran.r-project.org/web/packages/DiffCorr/vignettes/DiffCorr.html", "type": [ "Quick start guide" ], "note": null } ], "publication": [ { "doi": "10.1016/j.gene.2012.11.028", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "DiffCorr: An R package to analyze and visualize differential correlations in biological networks", "abstract": "Large-scale \"omics\" data, such as microarrays, can be used to infer underlying cellular regulatory networks in organisms, enabling us to better understand the molecular basis of disease and important traits. Correlation approaches, such as a hierarchical cluster analysis, have been widely used to analyze omics data. In addition to the changes in the mean levels of molecules in the omics data, it is important to know about the changes in the correlation relationship among molecules between 2 experimental conditions. The development of a tool to identify differential correlation patterns in omics data in an efficient and unbiased manner is therefore desirable. We developed the DiffCorr package, a simple method for identifying pattern changes between 2 experimental conditions in correlation networks, which builds on a commonly used association measure, such as Pearson's correlation coefficient. DiffCorr calculates correlation matrices for each dataset, identifies the first principal component-based \"eigen-molecules\" in the correlation networks, and tests differential correlation between the 2 groups based on Fisher's z-test. We illustrated its utility by demonstrating biologically relevant, differentially correlated molecules in transcriptome coexpression and metabolite-to-metabolite correlation networks. DiffCorr can explore differential correlations between 2 conditions in the context of post-genomics data types, namely transcriptomics and metabolomics. DiffCorr is simple to use in calculating differential correlations and is suitable for the first step towards inferring causal relationships and detecting biomarker candidates. The package can be downloaded from the following website: http://diffcorr.sourceforge.net/. © 2012 Elsevier B.V.", "date": "2013-04-10T00:00:00Z", "citationCount": 131, "authors": [ { "name": "Fukushima A." } ], "journal": "Gene" } } ], "credit": [ { "name": "Atsushi Fukushima", "email": "afukushima@kpu.ac.jp", "url": null, "orcidid": "http://orcid.org/0000-0001-9015-1694", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "atfukush", "additionDate": "2025-01-08T04:55:10.922667Z", "lastUpdate": "2025-01-08T05:23:17.072582Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "HEIDI", "description": "Linear mixed model based approach to partition the total heritability into the contributions of genomic regions.", "homepage": "http://genetics.cs.ucla.edu/heritability/", "biotoolsID": "heidi", "biotoolsCURIE": "biotools:heidi", 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"type": "Other", "note": "Mandatory annotation database", "version": "v5.1" } ], "documentation": [ { "url": "https://github.com/oschwengers/bakta/blob/main/README.md", "type": [ "General" ], "note": null }, { "url": "https://github.com/oschwengers/bakta/blob/main/CONTRIBUTION.md", "type": [ "Contributions policy" ], "note": null }, { "url": "https://github.com/oschwengers/bakta/blob/main/CODE_OF_CONDUCT.md", "type": [ "Code of conduct" ], "note": null }, { "url": "https://bakta.readthedocs.io/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1099/mgen.0.000685", "pmid": "34739369", "pmcid": "PMC8743544", "type": [ "Primary" ], "version": "1.1", "note": null, "metadata": { "title": "Bakta: Rapid and standardized annotation of bacterial genomes via alignment-free sequence identification", "abstract": "Command-line annotation software tools have continuously gained popularity compared to centralized online services due to the worldwide increase of sequenced bacterial genomes. However, results of existing command-line software pipelines heavily depend on taxon-specific databases or sufficiently well annotated reference genomes. Here, we introduce Bakta, a new command-line software tool for the robust, taxon-independent, thorough and, nonetheless, fast annotation of bacterial genomes. Bakta conducts a comprehensive annotation workflow including the detection of small proteins taking into account replicon metadata. The annotation of coding sequences is accelerated via an alignment-free sequence identification approach that in addition facilitates the precise assignment of public database cross-references. Annotation results are exported in GFF3 and International Nucleotide Sequence Database Collaboration (INSDC)-compliant flat files, as well as comprehensive JSON files, facilitating automated downstream analysis. We compared Bakta to other rapid contemporary command-line annotation software tools in both targeted and taxonomically broad benchmarks including isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms other tools in terms of functional annotations, the assignment of functional categories and database cross-references, whilst providing comparable wall-clock runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a GPLv3 license at https://github.com/oschwengers/bakta. An accompanying web version is available at https://bakta.computational.bio.", "date": "2021-01-01T00:00:00Z", "citationCount": 323, "authors": [ { "name": "Schwengers O." }, { "name": "Jelonek L." }, { "name": "Dieckmann M.A." }, { "name": "Beyvers S." }, { "name": "Blom J." }, { "name": "Goesmann A." } ], "journal": "Microbial Genomics" } } ], "credit": [ { "name": "Oliver Schwengers", "email": "oliver.schwengers@cb.jlug.de", "url": "https://github.com/oschwengers", "orcidid": "https://orcid.org/0000-0003-4216-2721", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "Justus Liebig University Giessen", "email": null, "url": "https://www.uni-giessen.de", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "oschwengers", "additionDate": "2021-05-08T17:25:21Z", "lastUpdate": "2024-12-23T21:48:50.049892Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-CZ", "bebatut" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Radiomics based Lung cancer staging", "description": "The model performs a classification of the patient using lung CT images. The classification is based on the National Comprehensive Cancer Network (NCCN) guidelines and provide a binary classification of the cancer stage, in class ‘0’ that includes patients with overall stage stage I and II and class ‘1’ that includes patients with overall stage III and IV4 (i.e. more severe, with different treatment).", "homepage": "https://www.med.auth.gr/en/content/laboratory-computing-medical-informatics-and-biomedical-imaging-technologies", "biotoolsID": "radiomics_based_lung_cancer_staging", "biotoolsCURIE": "biotools:radiomics_based_lung_cancer_staging", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_2640", "term": "Oncology" } ], "operatingSystem": [ "Linux" ], "language": [ "R", "Python" ], "license": "Not licensed", "collectionID": [ "EUCAIM" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Restricted access", "elixirPlatform": [ "Tools" ], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.5220/0011781500003414", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Ioanna Chouvarda", "email": "ioannach@auth.gr", "url": "https://scholar.google.com/citations?user=QgcrIzEAAAAJ&hl=el&oi=sra", "orcidid": "https://orcid.org/0000-0001-8915-6658", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": "Associate professor in Medical Informatics and Biomedical Data Analysis, at the Lab of Computing, Medical Informatics and Biomedical Imaging Technologies, School of Medicine, AUTH." } ], "owner": "dimfilos", "additionDate": "2024-12-19T13:50:24.941119Z", "lastUpdate": "2024-12-19T13:56:01.732738Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Multi-regional prostate segmentation tool", "description": "The tool performs an automatic multi-regional segmentation of the prostate into central-transition zone (CZ+TZ), peripheral zone (PZ), and seminal vesicle (SV) using a T2-weighted MRI image. A heterogeneous database of 243 T2-weighted prostate studies was used to train a U-Net based model with deep supervision.", "homepage": "https://quibim.com/es/qp-prostate/", "biotoolsID": "multi-regional_prostate_segmentation_tool", "biotoolsCURIE": "biotools:multi-regional_prostate_segmentation_tool", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3553", "term": "Image annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3442", "term": "MRI image" }, "format": [ { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] } ], "output": [], "note": "-i → input directory to the T2w MRI sequence containing .dcm files. \n-o → output directory to store the results.", "cmd": "python -m t2_prostate_segmentation -i [INPUT] -o [OUTPUT]" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" } ], "operatingSystem": [], "language": [ "Python" ], "license": "Proprietary", "collectionID": [ "EUCAIM" ], "maturity": "Mature", "cost": "Commercial", "accessibility": "Restricted access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://pubmed.ncbi.nlm.nih.gov/36690774/", "type": [ "Other" ], "note": "Publication" }, { "url": "https://quibim.com/es/qp-prostate/", "type": [ "Other" ], "note": "Product website." } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1007/s00330-023-09410-9", "pmid": "36690774", "pmcid": null, "type": [ "Primary" ], "version": "1.0.0", "note": null, "metadata": { "title": "Automated prostate multi-regional segmentation in magnetic resonance using fully convolutional neural networks", "abstract": "Objective: Automatic MR imaging segmentation of the prostate provides relevant clinical benefits for prostate cancer evaluation such as calculation of automated PSA density and other critical imaging biomarkers. Further, automated T2-weighted image segmentation of central-transition zone (CZ-TZ), peripheral zone (PZ), and seminal vesicle (SV) can help to evaluate clinically significant cancer following the PI-RADS v2.1 guidelines. Therefore, the main objective of this work was to develop a robust and reproducible CNN-based automatic prostate multi-regional segmentation model using an intercontinental cohort of prostate MRI. Methods: A heterogeneous database of 243 T2-weighted prostate studies from 7 countries and 10 machines of 3 different vendors, with the CZ-TZ, PZ, and SV regions manually delineated by two experienced radiologists (ground truth), was used to train (n = 123) and test (n = 120) a U-Net-based model with deep supervision using a cyclical learning rate. The performance of the model was evaluated by means of dice similarity coefficient (DSC), among others. Segmentation results with a DSC above 0.7 were considered accurate. Results: The proposed method obtained a DSC of 0.88 ± 0.01, 0.85 ± 0.02, 0.72 ± 0.02, and 0.72 ± 0.02 for the prostate gland, CZ-TZ, PZ, and SV respectively in the 120 studies of the test set when comparing the predicted segmentations with the ground truth. No statistically significant differences were found in the results obtained between manufacturers or continents. Conclusion: Prostate multi-regional T2-weighted MR images automatic segmentation can be accurately achieved by U-Net like CNN, generalizable in a highly variable clinical environment with different equipment, acquisition configurations, and population. Key Points: • Deep learning techniques allows the accurate segmentation of the prostate in three different regions on MR T2w images. • Multi-centric database proved the generalization of the CNN model on different institutions across different continents. • CNN models can be used to aid on the diagnosis and follow-up of patients with prostate cancer.", "date": "2023-07-01T00:00:00Z", "citationCount": 9, "authors": [ { "name": "Jimenez-Pastor A." }, { "name": "Lopez-Gonzalez R." }, { "name": "Fos-Guarinos B." }, { "name": "Garcia-Castro F." }, { "name": "Wittenberg M." }, { "name": "Torregrosa-Andres A." }, { "name": "Marti-Bonmati L." }, { "name": "Garcia-Fontes M." }, { "name": "Duarte P." }, { "name": "Gambini J.P." }, { "name": "Bittencourt L.K." }, { "name": "Kitamura F.C." }, { "name": "Venugopal V.K." }, { "name": "Mahajan V." }, { "name": "Ros P." }, { "name": "Soria-Olivas E." }, { "name": "Alberich-Bayarri A." } ], "journal": "European Radiology" } } ], "credit": [ { "name": "Alejandro Vergara Richart", "email": "alejandrovergara@quibim.com", "url": "https://quibim.com/es/", "orcidid": "https://orcid.org/0009-0003-5434-7499", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Support" ], "note": null } ], "owner": "alejandrovergara", "additionDate": "2024-12-19T08:54:13.149951Z", "lastUpdate": "2024-12-19T08:54:27.878162Z", "editPermission": { "type": "private", "authors": [ "alejandrovergara" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "RE-GOA", "description": "A tool for non-coding genomic regions functional enrichment analysis based on Regulatory Elements Gene Ontology Annotation (RE-GOA). Resources for RE-GOA in mouse and human are availible.", "homepage": "https://github.com/AMSSwanglab/RE-GOA", "biotoolsID": "re-goa", "biotoolsCURIE": "biotools:re-goa", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2436", "term": "Gene-set enrichment analysis" }, { "uri": "http://edamontology.org/operation_3672", "term": "Gene functional annotation" }, { "uri": "http://edamontology.org/operation_2437", "term": "Gene regulatory network prediction" }, { "uri": "http://edamontology.org/operation_1781", "term": "Gene regulatory network analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0749", "term": "Transcription factors and regulatory sites" }, { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" }, { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" }, { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_3169", "term": "ChIP-seq" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "Not licensed", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/BIOINFORMATICS/BTAC185", "pmid": "35561169", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Annotating regulatory elements by heterogeneous network embedding", "abstract": "Motivation: Regulatory elements (REs), such as enhancers and promoters, are known as regulatory sequences functional in a heterogeneous regulatory network to control gene expression by recruiting transcription regulators and carrying genetic variants in a context specific way. Annotating those REs relies on costly and labor-intensive next-generation sequencing and RNA-guided editing technologies in many cellular contexts. Results: We propose a systematic Gene Ontology Annotation method for Regulatory Elements (RE-GOA) by leveraging the powerful word embedding in natural language processing. We first assemble a heterogeneous network by integrating context specific regulations, protein-protein interactions and gene ontology (GO) terms. Then we perform network embedding and associate regulatory elements with GO terms by assessing their similarity in a low dimensional vector space. With three applications, we show that RE-GOA outperforms existing methods in annotating TFs' binding sites from ChIP-seq data, in functional enrichment analysis of differentially accessible peaks from ATAC-seq data, and in revealing genetic correlation among phenotypes from their GWAS summary statistics data.", "date": "2022-05-15T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Lu Y." }, { "name": "Feng Z." }, { "name": "Zhang S." }, { "name": "Wang Y." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Yurun Lu", "email": "luyurun@amss.ac.cn", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Yong Wang", "email": "ywang@amss.ac.cn", "url": null, "orcidid": "https://orcid.org/0000-0003-0695-5273", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Zhanying Feng", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-5727-3929", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Songmao Zhang", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "Jennifer", "additionDate": "2022-07-04T10:18:01.832399Z", "lastUpdate": "2024-12-18T09:59:55.399344Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "metaMDBG", "description": "MetaMDBG is a fast and low-memory assembler for long and accurate metagenomics reads (e.g. PacBio HiFi, Nanopore r10.4). It is based on the minimizer de-Brujin graph (MDBG), which have been reimplemetend specifically for metagenomics assembly. MetaMDBG combines an efficient multi-k approach in minimizer-space for dealing with uneven species coverages, and a novel abundance-based filtering method for simplifying strain complexity.", "homepage": "https://github.com/GaetanBenoitDev/metaMDBG", "biotoolsID": "metamdbg", "biotoolsCURIE": "biotools:metamdbg", "version": [ "1.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0525", "term": "Genome assembly" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [ "C++" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/GaetanBenoitDev/metaMDBG", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/GaetanBenoitDev/metaMDBG", "type": "Source code", "note": null, "version": "1.1" } ], "documentation": [ { "url": "https://github.com/GaetanBenoitDev/metaMDBG", "type": [ "Installation instructions" ], "note": null } ], "publication": [ { "doi": "10.1038/s41587-023-01983-6", "pmid": "38168989", "pmcid": "PMC11392814", "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "High-quality metagenome assembly from long accurate reads with metaMDBG", "abstract": "We introduce metaMDBG, a metagenomics assembler for PacBio HiFi reads. MetaMDBG combines a de Bruijn graph assembly in a minimizer space with an iterative assembly over sequences of minimizers to address variations in genome coverage depth and an abundance-based filtering strategy to simplify strain complexity. For complex communities, we obtained up to twice as many high-quality circularized prokaryotic metagenome-assembled genomes as existing methods and had better recovery of viruses and plasmids.", "date": "2024-09-01T00:00:00Z", "citationCount": 13, "authors": [ { "name": "Benoit G." }, { "name": "Raguideau S." }, { "name": "James R." }, { "name": "Phillippy A.M." }, { "name": "Chikhi R." }, { "name": "Quince C." } ], "journal": "Nature Biotechnology" } } ], "credit": [ { "name": "Gaetan Benoit", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "tcollins", "additionDate": "2024-12-17T20:42:26.939752Z", "lastUpdate": "2024-12-17T20:42:26.942889Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "wcloud", "description": "Converts a file from textual format into a word cloud image", 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"documentation": [], "publication": [], "credit": [], "owner": "robm", "additionDate": "2024-12-17T09:22:03.774590Z", "lastUpdate": "2024-12-17T09:22:03.777305Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "imzMLConverter", "description": "imzMLConverter is a tool designed to convert various mass spectrometry imaging (MSI) data formats into the open standard imzML format, enabling cross-platform data sharing and compatibility with different software and instruments.", "homepage": "https://github.com/AlanRace/imzMLConverter", "biotoolsID": "imzmlconverter", "biotoolsCURIE": "biotools:imzmlconverter", "version": [ "2.1.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3434", "term": "Conversion" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": 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"license": "BSD-3-Clause", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [], "credit": [], "owner": "sizhengZhao", "additionDate": "2024-09-11T13:33:41.280741Z", "lastUpdate": "2024-12-15T19:52:51.775402Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MorphPod", "description": "MorphPod: Deep learning phenotyping of Arabidopsis fruit morphology - \n\nDeep learning model weights and inference code to detect Arabidopsis thaliana siliques in scans of stem material. 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