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ArrayAnalysis.org provides researchers with an easy-to-use and comprehensive interface to the functionality of R and Bioconductor packages for microarray data analysis. As a modular open source project, it allows developers to contribute modules that provide support for additional types of data or extend workflows. Results: To enable data analysis of Illumina bead arrays for a broad user community, we have developed a module for ArrayAnalysis.org that provides a free and user-friendly web interface for quality control and pre-processing for these arrays. This module can be used together with existing modules for statistical and pathway analysis to provide a full workflow for Illumina gene expression data analysis. Conclusions: The Illumina bead arrays analysis module is available at http://www.arrayanalysis.org. A user guide, a tutorial demonstrating the analysis of an example dataset, and R scripts are available. 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In this report we highlight recently added features enabling biomedical analyses on a large scale.", "date": "2016-07-08T00:00:00Z", "citationCount": 1477, "authors": [ { "name": "Afgan E." }, { "name": "Baker D." }, { "name": "van den Beek M." }, { "name": "Blankenberg D." }, { "name": "Bouvier D." }, { "name": "Cech M." }, { "name": "Chilton J." }, { "name": "Clements D." }, { "name": "Coraor N." }, { "name": "Eberhard C." }, { "name": "Gruning B." }, { "name": "Guerler A." }, { "name": "Hillman-Jackson J." }, { "name": "Kuster G.V." }, { "name": "Rasche E." }, { "name": "Soranzo N." }, { "name": "Turaga N." }, { "name": "Taylor J." }, { "name": "Nekrutenko A." }, { "name": "Goecks J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.7490/f1000research.1114334.1", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Galaxy Support Team", "email": "galaxy@pasteur.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "hmenager", "additionDate": "2016-12-19T14:22:09Z", "lastUpdate": "2025-08-27T10:49:28.510179Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "fqconvert", "description": "Convert quality scoring to Sanger in FASTQ files.", "homepage": "http://ftp.pasteur.fr/pub/gensoft/projects/fqtools/README", "biotoolsID": "fqconvert", "biotoolsCURIE": "biotools:fqconvert", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0233", "term": "Sequence conversion" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_1933", "term": "FASTQ-solexa" }, { "uri": "http://edamontology.org/format_1931", "term": "FASTQ-illumina" }, { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_1932", "term": "FASTQ-sanger" } ] }, { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "galaxyPasteur", "Institut Pasteur", "fqtools" ], "maturity": "Mature", "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://galaxy.pasteur.fr/tool_runner?tool_id=toolshed.pasteur.fr/repos/fmareuil/fqconvert2/fqconvert/1.0.0", "type": [ "Galaxy service" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkw343", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update", "abstract": "High-throughput data production technologies, particularly ‘next-generation’ DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. 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Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. In this report we highlight recently added features enabling biomedical analyses on a large scale.", "date": "2016-07-08T00:00:00Z", "citationCount": 1477, "authors": [ { "name": "Afgan E." }, { "name": "Baker D." }, { "name": "van den Beek M." }, { "name": "Blankenberg D." }, { "name": "Bouvier D." }, { "name": "Cech M." }, { "name": "Chilton J." }, { "name": "Clements D." }, { "name": "Coraor N." }, { "name": "Eberhard C." }, { "name": "Gruning B." }, { "name": "Guerler A." }, { "name": "Hillman-Jackson J." }, { "name": "Kuster G.V." }, { "name": "Rasche E." }, { "name": "Soranzo N." }, { "name": "Turaga N." }, { "name": "Taylor J." }, { "name": "Nekrutenko A." }, { "name": "Goecks J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.7490/f1000research.1114334.1", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Galaxy Support Team", "email": "galaxy@pasteur.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "hmenager", "additionDate": "2016-12-19T14:27:26Z", "lastUpdate": "2025-08-27T10:47:14.412802Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "FJD-pipeline", "description": "Pipeline for Single Nucleotide Variants (SNVs) and Copy Number Variation (CNVs) variant calling. This tool is no longer maintained. See the new version: PARROT-FJD.", "homepage": "https://github.com/TBLabFJD/VariantCallingFJD", "biotoolsID": "fjd-pipeline", "biotoolsCURIE": "biotools:fjd-pipeline", "version": [], "otherID": [], "relation": [ { "biotoolsID": "priorr", "type": "usedBy" }, { "biotoolsID": "parrot-fjd", "type": "hasNewVersion" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3227", "term": "Variant calling" }, { "uri": "http://edamontology.org/operation_3961", "term": "Copy number variation detection" }, { "uri": "http://edamontology.org/operation_0362", "term": "Genome annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1193", "term": "Tool name (FASTA)" }, "format": [ { "uri": "http://edamontology.org/format_2545", "term": "FASTQ-like format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [ { "uri": "http://edamontology.org/format_3016", "term": "VCF" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" } ], "operatingSystem": [ "Linux" ], "language": [ "Python", "R", "Bash" ], "license": "CC-BY-NC-SA-4.0", "collectionID": [ "IMPaCT-Data" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/TBLabFJD/VariantCallingFJD", "type": [ "Repository" ], "note": "GitHub repository" } ], "download": [], "documentation": [ { "url": "https://github.com/TBLabFJD/VariantCallingFJD", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1038/s41525-021-00278-6", "pmid": "35087072", "pmcid": "PMC8795168", "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "An evaluation of pipelines for DNA variant detection can guide a reanalysis protocol to increase the diagnostic ratio of genetic diseases", "abstract": "Clinical exome (CE) sequencing has become a first-tier diagnostic test for hereditary diseases; however, its diagnostic rate is around 30–50%. In this study, we aimed to increase the diagnostic yield of CE using a custom reanalysis algorithm. Sequencing data were available for three cohorts using two commercial protocols applied as part of the diagnostic process. Using these cohorts, we compared the performance of general and clinically relevant variant calling and the efficacy of an in-house bioinformatic protocol (FJD-pipeline) in detecting causal variants as compared to commercial protocols. On the whole, the FJD-pipeline detected 99.74% of the causal variants identified by the commercial protocol in previously solved cases. In the unsolved cases, FJD-pipeline detects more INDELs and non-exonic variants, and is able to increase the diagnostic yield in 2.5% and 3.2% in the re-analysis of 78 cancer and 62 cardiovascular cases. These results were considered to design a reanalysis, filtering and prioritization algorithm that was tested by reassessing 68 inconclusive cases of monoallelic autosomal recessive retinal dystrophies increasing the diagnosis by 4.4%. In conclusion, a guided NGS reanalysis of unsolved cases increases the diagnostic yield in genetic disorders, making it a useful diagnostic tool in medical genetics.", "date": "2022-12-01T00:00:00Z", "citationCount": 12, "authors": [ { "name": "Romero R." }, { "name": "de la Fuente L." }, { "name": "Del Pozo-Valero M." }, { "name": "Riveiro-Alvarez R." }, { "name": "Trujillo-Tiebas M.J." }, { "name": "Martin-Merida I." }, { "name": "Avila-Fernandez A." }, { "name": "Iancu I.-F." }, { "name": "Perea-Romero I." }, { "name": "Nunez-Moreno G." }, { "name": "Damian A." }, { "name": "Rodilla C." }, { "name": "Almoguera B." }, { "name": "Corton M." }, { "name": "Ayuso C." }, { "name": "Minguez P." } ], "journal": "npj Genomic Medicine" } } ], "credit": [ { "name": "Bioinformatics Unit IIS-FJD", "email": "pablo.minguez@quironsalud.es", "url": "https://www.translationalbioinformaticslab.es/", "orcidid": "https://orcid.org/0000-0003-4099-9421", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "iiancu", "additionDate": "2022-03-21T17:29:40.559556Z", "lastUpdate": "2025-08-12T08:31:29.574795Z", "editPermission": { "type": "group", "authors": [ "gonumo", "pminguez", "yolandabq" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Beyond Venetoclax Cryptic Pocket Pipeline", "description": "A machine-guided pipeline for cryptic pocket discovery in undruggable cancer targets. Combines long MD (100–200 ns), metastable state modeling (MSM), hydration thermodynamics, and PLIP-based interaction analysis to identify mutant-specific pockets absent in wild-type. Validated on TP53, KRAS G12D, MYC mutants, and fusion oncoproteins", "homepage": "https://sites.google.com/view/sn-biotech/home\"", "biotoolsID": "beyond_venetoclax_cryptic_pocket_pipeline", "biotoolsCURIE": "biotools:beyond_venetoclax_cryptic_pocket_pipeline", "version": [ "v1.0 (2025 release)" ], "otherID": [], "relation": [ { "biotoolsID": "gromacs", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2423", "term": "Prediction and recognition" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0883", "term": "Structure" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3842", "term": "Molecular simulation data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0883", "term": "Structure" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2087", "term": "Molecular property" }, "format": [] } ], "note": "PLIP results, pocket volume, CryptoSite, Fpocket outputs,", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0883", "term": "Structure" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3842", "term": "Molecular simulation data" }, "format": [] } ], "note": "run md on structure", "cmd": null } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3678", "term": "Experimental design and studies" }, { "uri": "http://edamontology.org/topic_4019", "term": "Biosciences" } ], "operatingSystem": [], "language": [ "Bash", "Python", "PyMOL", "Other" ], "license": "Proprietary", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge (with restrictions)", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://chemrxiv.org/engage/chemrxiv/article-details/688744d6728bf9025e9ce1c2", "type": [ "Other" ], "note": "Describes the Beyond Venetoclax cryptic pocket pipeline for undruggable cancer targets." } ], "download": [ { "url": "https://chemrxiv.org/engage/chemrxiv/article-details/688744d6728bf9025e9ce1c2", "type": "Downloads page", "note": "Contains preprint with full pipeline description and figure references.", "version": "v1.0 (2025 release)" } ], "documentation": [ { "url": "https://chemrxiv.org/engage/chemrxiv/article-details/688744d6728bf9025e9ce1c2", "type": [ "Other" ], "note": "Contains preprint with full pipeline description and figure references." } ], "publication": [ { "doi": "10.26434/chemrxiv-2025-5vz5r", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": "v1.0 (2025 release)", "note": "Contains preprint with full pipeline description and figure references.", "metadata": null } ], "credit": [ { "name": "Hoosdally", "email": "shoosdally@moemu.org", "url": "https://sites.google.com/view/sn-biotech/home", "orcidid": "https://orcid.org/0009-0008-4144-718X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Shakeelh", "additionDate": "2025-08-01T05:53:13.245244Z", "lastUpdate": "2025-08-01T07:14:43.102445Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "MaCPepDB - Mass Centric Peptide Database", "description": "A Database to Quickly Access All Tryptic Peptides of the UniProtKB", "homepage": "https://macpepdb.cubimed.rub.de/", "biotoolsID": "macpepdb_-_mass_centric_peptide_database", "biotoolsCURIE": "biotools:macpepdb_-_mass_centric_peptide_database", "version": [ "3.0.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [], "language": [ "Rust", "JavaScript", "Other" ], "license": null, "collectionID": [ "CUBiMed.RUB", "BioInfra.Prot" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/medbioinf/macpepdb", "type": [ "Repository" ], "note": "Backend implementation written in Rust / Axum" }, { "url": "https://github.com/medbioinf/macpepdb-frontend", "type": [ "Repository" ], "note": "Frontend implementation written in Rust / Dioxus" } ], "download": [], "documentation": [ { "url": "https://docs.rs/macpepdb/latest/macpepdb/web/index.html", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jproteome.0c00967", "pmid": "33724838", "pmcid": null, "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "MaCPepDB: A Database to Quickly Access All Tryptic Peptides of the UniProtKB", "abstract": "Protein sequence databases play a crucial role in the majority of the currently applied mass-spectrometry-based proteomics workflows. Here UniProtKB serves as one of the major sources, as it combines the information of several smaller databases and enriches the entries with additional biological information. For the identification of peptides in a sample by tandem mass spectra, as generated by data-dependent acquisition, protein sequence databases provide the basis for most spectrum identification search engines. In addition, for targeted proteomics approaches like selected reaction monitoring (SRM) and parallel reaction monitoring (PRM), knowledge of the peptide sequences, their masses, and whether they are unique for a protein is essential. Because most bottom-up proteomics approaches use trypsin to cleave the proteins in a sample, the tryptic peptides contained in a protein database are of great interest. We present a database, called MaCPepDB (mass-centric peptide database), that consists of the complete tryptic digest of the Swiss-Prot and TrEMBL parts of UniProtKB. This database is especially designed to not only allow queries of peptide sequences and return the respective information about connected proteins and thus whether a peptide is unique but also allow queries of specific masses of peptides or precursors of MS/MS spectra. Furthermore, posttranslational modifications can be considered in a query as well as different mass deviations for posttranslational modifications. Hence the database can be used by a sequence query not only to, for example, check in which proteins of the UniProt database a tryptic peptide can be found but also to find possibly interfering peptides in PRM/SRM experiments using the mass query. The complete database contains currently 5 939 244 990 peptides from 185 561 610 proteins (UniProt version 2020_03), for which a single query usually takes less than 1 s. For easy exploration of the data, a web interface was developed. A REST application programming interface (API) for programmatic and workflow access is also available at https://macpepdb.mpc.rub.de.", "date": "2021-04-02T00:00:00Z", "citationCount": 9, "authors": [ { "name": "Uszkoreit J." }, { "name": "Winkelhardt D." }, { "name": "Barkovits K." }, { "name": "Wulf M." }, { "name": "Roocke S." }, { "name": "Marcus K." }, { "name": "Eisenacher M." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Julian Uszkoreit", "email": null, "url": null, "orcidid": "http://orcid.org/0000-0001-7522-4007", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Dirk Winkelhardt", "email": "dirk.winkelhardt@rub.de", "url": null, "orcidid": "https://orcid.org/0000-0001-8770-2221", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "PD Dr. Martin Eisenacher", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-2687-7444", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "di_hardt", "additionDate": "2023-07-25T12:35:27.605861Z", "lastUpdate": "2025-07-31T09:03:29.192901Z", "editPermission": { "type": "group", "authors": [ "di_hardt", "julianu", "BioInfra.Prot" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "WheatIS", "description": "This project aims at building an International Wheat Information System (WheatIS) to support the wheat research community. The main objective is to provide a single-access web based system to access to the available data resources and bioinformatics tools. The web portal indexes and makes findable any kind of data from wheat related species. \nThe WheatIS search is an implementation of DataDiscovery.", "homepage": "https://urgi.versailles.inrae.fr/wheatis/", "biotoolsID": "WheatIS", "biotoolsCURIE": "biotools:WheatIS", "version": [], "otherID": [], "relation": [ { "biotoolsID": "gnpis", "type": "uses" }, { "biotoolsID": "DataDiscovery", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_3625", "term": "Relation extraction" }, { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" }, { "uri": "http://edamontology.org/operation_3908", "term": "Information retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0968", "term": "Keyword" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2093", "term": "Data reference" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web API", "Web application", "Web service", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_0610", "term": "Ecology" }, { "uri": "http://edamontology.org/topic_3071", "term": "Biological databases" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3810", "term": "Agricultural science" } ], "operatingSystem": [], "language": [], "license": "BSD-3-Clause", "collectionID": [ "elixir-fr-sdp-2019", "URGI" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools", "Data", "Interoperability" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [ { "url": "http://www.wheatis.org/", "type": [ "Other" ], "note": "WheatIS website" } ], "download": [], "documentation": [ { "url": "https://urgi.versailles.inra.fr/wheatis/about", "type": [ "General" ], "note": null }, { "url": "https://urgi.versailles.inra.fr/wheatis/join", "type": [ "Contributions policy" ], "note": null }, { "url": "https://urgi.versailles.inra.fr/wheatis/legal", "type": [ "Terms of use" ], "note": null }, { "url": "https://urgi.versailles.inra.fr/wheatis/help", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1186/s13059-018-1491-4", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": "Alaux M, Rogers J, Letellier T, Flores R, Alfama F, Pommier C, Mohellibi N, Durand S, Kimmel E, Michotey C, Guerche C, Loaec M, Lainé M, Steinbach D, Choulet F, Rimbert H, Leroy P, Guilhot N, Salse J, Feuillet C, International Wheat Genome Sequencing Consortium, Paux E, Eversole K, Adam-Blondon A-F, Quesneville H (2018) Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data. Genome Biology, 19:111", "metadata": { "title": "Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data", "abstract": "© 2018 The Author(s).The Wheat@URGI portal has been developed to provide the international community of researchers and breeders with access to the bread wheat reference genome sequence produced by the International Wheat Genome Sequencing Consortium. Genome browsers, BLAST, and InterMine tools have been established for in-depth exploration of the genome sequence together with additional linked datasets including physical maps, sequence variations, gene expression, and genetic and phenomic data from other international collaborative projects already stored in the GnpIS information system. The portal provides enhanced search and browser features that will facilitate the deployment of the latest genomics resources in wheat improvement.", "date": "2018-08-17T00:00:00Z", "citationCount": 88, "authors": [ { "name": "Alaux M." }, { "name": "Rogers J." }, { "name": "Letellier T." }, { "name": "Flores R." }, { "name": "Alfama F." }, { "name": "Pommier C." }, { "name": "Mohellibi N." }, { "name": "Durand S." }, { "name": "Kimmel E." }, { "name": "Michotey C." }, { "name": "Guerche C." }, { "name": "Loaec M." }, { "name": "Laine M." }, { "name": "Steinbach D." }, { "name": "Choulet F." }, { "name": "Rimbert H." }, { "name": "Leroy P." }, { "name": "Guilhot N." }, { "name": "Salse J." }, { "name": "Feuillet C." }, { "name": "Paux E." }, { "name": "Eversole K." }, { "name": "Adam-Blondon A.-F." }, { "name": "Quesneville H." } ], "journal": "Genome Biology" } } ], "credit": [ { "name": "Support service", "email": "urgi-support@inrae.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact", "Support" ], "note": null } ], "owner": "jison", "additionDate": "2019-11-05T10:40:37Z", "lastUpdate": "2025-07-29T13:42:41.391722Z", "editPermission": { "type": "group", "authors": [ "nfrancillon", "raphael.flores", "cmichotey" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DataDiscovery", "description": "DataDiscovery aims at providing researchers a simple and fast access to relevant biological data using specific keywords and easy to use filters.\n\nThis tool is expected to be easily customizable for specific filters, environments, or data schemas. Its current implementations supported by URGI are: WheatIS, Plant, RARe.", "homepage": "https://urgi.versailles.inrae.fr/data-discovery/", "biotoolsID": "DataDiscovery", "biotoolsCURIE": "biotools:DataDiscovery", "version": [], "otherID": [], "relation": [ { "biotoolsID": "wheatis", "type": "usedBy" }, { "biotoolsID": "RARe", "type": "usedBy" }, { "biotoolsID": "Plant_DataDiscovery", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_3625", "term": "Relation extraction" }, { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" }, { "uri": "http://edamontology.org/operation_3908", "term": "Information retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0968", "term": "Keyword" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2093", "term": "Data reference" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web API", "Web application", "Web service", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_0610", "term": "Ecology" }, { "uri": "http://edamontology.org/topic_3071", "term": "Biological databases" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3810", "term": "Agricultural science" } ], "operatingSystem": [ "Linux" ], "language": [ "JavaScript", "Java", "Bash" ], "license": "BSD-3-Clause", "collectionID": [ "elixir-fr-sdp-2019", "URGI" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data", "Tools", "Interoperability" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [ { "url": "https://forgemia.inra.fr/urgi-is/data-discovery", "type": [ "Repository" ], "note": "GitLab code repository for DataDiscovery" }, { "url": "https://github.com/gnpis/DataDiscovery/", "type": [ "Mirror" ], "note": "Code repository mirror link for DataDiscovery" } ], "download": [], "documentation": [ { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/LEGAL-MENTIONS.md", "type": [ "Terms of use" ], "note": "General terms of use" }, { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/README.md#contribute", "type": [ "Contributions policy" ], "note": "How to contribute" }, { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/HELP.md", "type": [ "User manual" ], "note": "How to use" }, { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/README.md#setup", "type": [ "Installation instructions" ], "note": "How to install" } ], "publication": [ { "doi": "10.3835/plantgenome2015.06.0038", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": "1-\tSpannagl, M., Alaux, M., Lange, M., Bolser, D. M., Bader, K. C., Letellier, T., Kimmel, E., Flores, R.-G., Pommier, C., Kerhornou, A., Walts, B., Nussbaumer, T., Grabmuller, C., Chen, J., Colmsee, C., Beier, S., Mascher, M., Schmutzer, T., Arend, D., Thanki, A., Ramirez-Gonzalez, R., Ayling, M., Ayling, S., Caccamo, M., Mayer, K. F. X., Scholz, U., Steinbach, D., Quesneville, H., Kersey, P. (2016). TransPLANT resources for triticeae genomic data. Plant Genome, 9 (1), 13 p.", "metadata": { "title": "TransPLANT resources for triticeae genomic data", "abstract": "The genome sequences of many important Triticeae species, including bread wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), remained uncharacterized for a long time because their high repeat content, large sizes, and polyploidy. As a result of improvements in sequencing technologies and novel analyses strategies, several of these have recently been deciphered. These efforts have generated new insights into Triticeae biology and genome organization and have important implications for downstream usage by breeders, experimental biologists, and comparative genomicists. transPLANT (http://www.transplantdb.eu) is an EU-funded project aimed at constructing hardware, software, and data infrastructure for genome-scale research in the life sciences. Since the Triticeae data are intrinsically complex, heterogenous, and distributed, the transPLANT consortium has undertaken efforts to develop common data formats and tools that enable the exchange and integration of data from distributed resources. Here we present an overview of the individual Triticeae genome resources hosted by transPLANT partners, introduce the objectives of transPLANT, and outline common developments and interfaces supporting integrated data access.", "date": "2016-03-01T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Spannagl M." }, { "name": "Alaux M." }, { "name": "Lange M." }, { "name": "Bolser D.M." }, { "name": "Bader K.C." }, { "name": "Letellier T." }, { "name": "Kimmel E." }, { "name": "Flores R." }, { "name": "Pommier C." }, { "name": "Kerhornou A." }, { "name": "Walts B." }, { "name": "Nussbaumer T." }, { "name": "Grabmuller C." }, { "name": "Chen J." }, { "name": "Colmsee C." }, { "name": "Beier S." }, { "name": "Mascher M." }, { "name": "Schmutzer T." }, { "name": "Arend D." }, { "name": "Thanki A." }, { "name": "Ramirez-Gonzalez R." }, { "name": "Ayling M." }, { "name": "Ayling S." }, { "name": "Caccamo M." }, { "name": "Mayer K.F.X." }, { "name": "Scholz U." }, { "name": "Steinbach D." }, { "name": "Quesneville H." }, { "name": "Kersey P.J." } ], "journal": "Plant Genome" } }, { "doi": "10.1038/hortres.2016.56", "pmid": null, "pmcid": null, "type": [], "version": null, "note": "2-\tAdam-Blondon, A.-F., Alaux, M., Pommier, C., Cantu, D., Cheng, Z.-M., Cramer, G. R., Davies, C., Delrot, S., Deluc, L., di Gaspero, G., Grimplet, J., Fennell, A., Londo, J. P., Kersey, P., Mattivi, F., Naithani, S., Neveu, P., Nikolski, M., Pezzotti, M., Reisch, B. I., Topfer, R., Vivier, M., Ware, D., Quesneville, H. (2016). Towards an open grapevine information system. Horticulture Research, 3, 8 p. , DOI : 10.1038/hortres.2016.56", "metadata": { "title": "Towards an open grapevine information system", "abstract": "Viticulture, like other fields of agriculture, is currently facing important challenges that will be addressed only through sustained, dedicated and coordinated research. Although the methods used in biology have evolved tremendously in recent years and now involve the routine production of large data sets of varied nature, in many domains of study, including grapevine research, there is a need to improve the findability, accessibility, interoperability and reusability (FAIR-ness) of these data. Considering the heterogeneous nature of the data produced, the transnational nature of the scientific community and the experience gained elsewhere, we have formed an open working group, in the framework of the International Grapevine Genome Program (www.vitaceae.org), to construct a coordinated federation of information systems holding grapevine data distributed around the world, providing an integrated set of interfaces supporting advanced data modeling, rich semantic integration and the next generation of data mining tools. To achieve this goal, it will be critical to develop, implement and adopt appropriate standards for data annotation and formatting. The development of this system, the GrapeIS, linking genotypes to phenotypes, and scientific research to agronomical and oeneological data, should provide new insights into grape biology, and allow the development of new varieties to meet the challenges of biotic and abiotic stress, environmental change, and consumer demand.", "date": "2016-11-23T00:00:00Z", "citationCount": 37, "authors": [ { "name": "Adam-Blondon A.-F." }, { "name": "Alaux M." }, { "name": "Pommier C." }, { "name": "Cantu D." }, { "name": "Cheng Z.-M." }, { "name": "Cramer G." }, { "name": "Davies C." }, { "name": "Delrot S." }, { "name": "Deluc L." }, { "name": "Di Gaspero G." }, { "name": "Grimplet J." }, { "name": "Fennell A." }, { "name": "Londo J." }, { "name": "Kersey P." }, { "name": "Mattivi F." }, { "name": "Naithani S." }, { "name": "Neveu P." }, { "name": "Nikolski M." }, { "name": "Pezzotti M." }, { "name": "Reisch B." }, { "name": "Topfer R." }, { "name": "Vivier M." }, { "name": "Ware D." }, { "name": "Quesneville H." } ], "journal": "Horticulture Research" } }, { "doi": "10.1186/s13059-018-1491-4", "pmid": null, "pmcid": null, "type": [], "version": null, "note": "3-\tAlaux M, Rogers J, Letellier T, Flores R, Alfama F, Pommier C, Mohellibi N, Durand S, Kimmel E, Michotey C, Guerche C, Loaec M, Lainé M, Steinbach D, Choulet F, Rimbert H, Leroy P, Guilhot N, Salse J, Feuillet C, International Wheat Genome Sequencing Consortium, Paux E, Eversole K, Adam-Blondon A-F, Quesneville H (2018) Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data. Genome Biology, 19:111.", "metadata": { "title": "Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data", "abstract": "The Wheat@URGI portal has been developed to provide the international community of researchers and breeders with access to the bread wheat reference genome sequence produced by the International Wheat Genome Sequencing Consortium. Genome browsers, BLAST, and InterMine tools have been established for in-depth exploration of the genome sequence together with additional linked datasets including physical maps, sequence variations, gene expression, and genetic and phenomic data from other international collaborative projects already stored in the GnpIS information system. The portal provides enhanced search and browser features that will facilitate the deployment of the latest genomics resources in wheat improvement.", "date": "2018-08-17T00:00:00Z", "citationCount": 181, "authors": [ { "name": "Alaux M." }, { "name": "Rogers J." }, { "name": "Letellier T." }, { "name": "Flores R." }, { "name": "Alfama F." }, { "name": "Pommier C." }, { "name": "Mohellibi N." }, { "name": "Durand S." }, { "name": "Kimmel E." }, { "name": "Michotey C." }, { "name": "Guerche C." }, { "name": "Loaec M." }, { "name": "Laine M." }, { "name": "Steinbach D." }, { "name": "Choulet F." }, { "name": "Rimbert H." }, { "name": "Leroy P." }, { "name": "Guilhot N." }, { "name": "Salse J." }, { "name": "Feuillet C." }, { "name": "Paux E." }, { "name": "Eversole K." }, { "name": "Adam-Blondon A.-F." }, { "name": "Quesneville H." } ], "journal": "Genome Biology" } } ], "credit": [ { "name": "urgi-support", "email": "urgi-support@inrae.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact", "Support" ], "note": null } ], "owner": "nfrancillon", "additionDate": "2020-01-21T16:40:38Z", "lastUpdate": "2025-07-29T13:42:39.375595Z", "editPermission": { "type": "group", "authors": [ "urgi-contact", "cpommier", "cmichotey", "erlefloch", "raphael.flores" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Genetic and Genomic Information System (GnpIS)", "description": "A multispecies integrative information system dedicated to plant and fungi pests.. It allows researchers to access genetic, phenotypic and genomic data. It is used by both large international projects and the French National Research Institute for Agriculture, Food and Environment", "homepage": "https://urgi.versailles.inrae.fr/gnpis", "biotoolsID": "gnpis", "biotoolsCURIE": "biotools:gnpis", "version": [ "18.2" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3208", "term": "Genome visualisation" }, { "uri": "http://edamontology.org/operation_2409", "term": "Data handling" }, { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" }, { "uri": "http://edamontology.org/operation_3559", "term": "Ontology visualisation" } ], "input": [], "output": [ { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0850", "term": "Sequence set" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1255", "term": "Sequence features" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0920", "term": "Genotype/phenotype report" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_3053", "term": "Genetics" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript", "C#" ], "license": "CC-BY-4.0", "collectionID": [ "elixir-fr-sdp-2019", "Animal and Crop Genomics" ], "maturity": "Mature", "cost": null, "accessibility": "Restricted access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://urgi.versailles.inra.fr/gnpis/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/database/bat058", "pmid": "23959375", "pmcid": "PMC3746681", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "GnpIS: An information system to integrate genetic and genomic data from plants and fungi", "abstract": "Data integration is a key challenge for modern bioinformatics. It aims to provide biologists with tools to explore relevant data produced by different studies. Large-scale international projects can generate lots of heterogeneous and unrelated data. The challenge is to integrate this information with other publicly available data. Nucleotide sequencing throughput has been improved with new technologies; this increases the need for powerful information systems able to store, manage and explore data. GnpIS is a multispecies integrative information system dedicated to plant and fungi pests. It bridges genetic and genomic data, allowing researchers access to both genetic information (e.g. genetic maps, quantitative trait loci, markers, single nucleotide polymorphisms, germplasms and genotypes) and genomic data (e.g. genomic sequences, physical maps, genome annotation and expression data) for species of agronomical interest. GnpIS is used by both large international projects and plant science departments at the French National Institute for Agricultural Research. Here, we illustrate its use. © The Author(s) 2013. Published by Oxford University Press.", "date": "2013-12-01T00:00:00Z", "citationCount": 42, "authors": [ { "name": "Steinbach D." }, { "name": "Alaux M." }, { "name": "Amselem J." }, { "name": "Choisne N." }, { "name": "Durand S." }, { "name": "Flores R." }, { "name": "Keliet A.-O." }, { "name": "Kimmel E." }, { "name": "Lapalu N." }, { "name": "Luyten I." }, { "name": "Michotey C." }, { "name": "Mohellibi N." }, { "name": "Pommier C." }, { "name": "Reboux S." }, { "name": "Valdenaire D." }, { "name": "Verdelet D." }, { "name": "Quesneville H." } ], "journal": "Database" } }, { "doi": "10.1007/978-1-4939-6658-5_5", "pmid": "27987166", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Mining plant genomic and genetic data using the gnpis information system", "abstract": "GnpIS is an information system designed to help scientists working on plants and fungi to decipher the molecular and genetic architecture of trait variations by facilitating the navigation through genetic, genomic, and phenotypic information. The purpose of the present chapter is to illustrate how users can (1) explore datasets from phenotyping experiments in order to build new datasets for studying genotype × environment interactions in traits, (2) browse into the results of other genetic analysis data such as GWAS to generate or check working hypothesis about candidate genes or to identify important alleles and germplasms for breeding programs, and (3) explore the polymorphism in specific area of the genome using InterMine, JBrowse tools embedded in the GnpIS information system.", "date": "2017-01-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Adam-Blondon A.-F." }, { "name": "Alaux M." }, { "name": "Durand S." }, { "name": "Letellier T." }, { "name": "Merceron G." }, { "name": "Mohellibi N." }, { "name": "Pommier C." }, { "name": "Steinbach D." }, { "name": "Alfama F." }, { "name": "Amselem J." }, { "name": "Charruaud D." }, { "name": "Choisne N." }, { "name": "Flores R." }, { "name": "Guerche C." }, { "name": "Jamilloux V." }, { "name": "Kimmel E." }, { "name": "Lapalu N." }, { "name": "Loaec M." }, { "name": "Michotey C." }, { "name": "Quesneville H." } ], "journal": "Methods in Molecular Biology" } }, { "doi": "10.1038/hortres.2016.56", "pmid": "27917288", "pmcid": "PMC5120350", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Towards an open grapevine information system", "abstract": "Viticulture, like other fields of agriculture, is currently facing important challenges that will be addressed only through sustained, dedicated and coordinated research. Although the methods used in biology have evolved tremendously in recent years and now involve the routine production of large data sets of varied nature, in many domains of study, including grapevine research, there is a need to improve the findability, accessibility, interoperability and reusability (FAIR-ness) of these data. Considering the heterogeneous nature of the data produced, the transnational nature of the scientific community and the experience gained elsewhere, we have formed an open working group, in the framework of the International Grapevine Genome Program (www.vitaceae.org), to construct a coordinated federation of information systems holding grapevine data distributed around the world, providing an integrated set of interfaces supporting advanced data modeling, rich semantic integration and the next generation of data mining tools. To achieve this goal, it will be critical to develop, implement and adopt appropriate standards for data annotation and formatting. The development of this system, the GrapeIS, linking genotypes to phenotypes, and scientific research to agronomical and oeneological data, should provide new insights into grape biology, and allow the development of new varieties to meet the challenges of biotic and abiotic stress, environmental change, and consumer demand.", "date": "2016-11-23T00:00:00Z", "citationCount": 37, "authors": [ { "name": "Adam-Blondon A.-F." }, { "name": "Alaux M." }, { "name": "Pommier C." }, { "name": "Cantu D." }, { "name": "Cheng Z.-M." }, { "name": "Cramer G." }, { "name": "Davies C." }, { "name": "Delrot S." }, { "name": "Deluc L." }, { "name": "Di Gaspero G." }, { "name": "Grimplet J." }, { "name": "Fennell A." }, { "name": "Londo J." }, { "name": "Kersey P." }, { "name": "Mattivi F." }, { "name": "Naithani S." }, { "name": "Neveu P." }, { "name": "Nikolski M." }, { "name": "Pezzotti M." }, { "name": "Reisch B." }, { "name": "Topfer R." }, { "name": "Vivier M." }, { "name": "Ware D." }, { "name": "Quesneville H." } ], "journal": "Horticulture Research" } }, { "doi": "10.3835/plantgenome2015.06.0038", "pmid": "27898761", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "TransPLANT resources for triticeae genomic data", "abstract": "The genome sequences of many important Triticeae species, including bread wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), remained uncharacterized for a long time because their high repeat content, large sizes, and polyploidy. As a result of improvements in sequencing technologies and novel analyses strategies, several of these have recently been deciphered. These efforts have generated new insights into Triticeae biology and genome organization and have important implications for downstream usage by breeders, experimental biologists, and comparative genomicists. transPLANT (http://www.transplantdb.eu) is an EU-funded project aimed at constructing hardware, software, and data infrastructure for genome-scale research in the life sciences. Since the Triticeae data are intrinsically complex, heterogenous, and distributed, the transPLANT consortium has undertaken efforts to develop common data formats and tools that enable the exchange and integration of data from distributed resources. Here we present an overview of the individual Triticeae genome resources hosted by transPLANT partners, introduce the objectives of transPLANT, and outline common developments and interfaces supporting integrated data access.", "date": "2016-03-01T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Spannagl M." }, { "name": "Alaux M." }, { "name": "Lange M." }, { "name": "Bolser D.M." }, { "name": "Bader K.C." }, { "name": "Letellier T." }, { "name": "Kimmel E." }, { "name": "Flores R." }, { "name": "Pommier C." }, { "name": "Kerhornou A." }, { "name": "Walts B." }, { "name": "Nussbaumer T." }, { "name": "Grabmuller C." }, { "name": "Chen J." }, { "name": "Colmsee C." }, { "name": "Beier S." }, { "name": "Mascher M." }, { "name": "Schmutzer T." }, { "name": "Arend D." }, { "name": "Thanki A." }, { "name": "Ramirez-Gonzalez R." }, { "name": "Ayling M." }, { "name": "Ayling S." }, { "name": "Caccamo M." }, { "name": "Mayer K.F.X." }, { "name": "Scholz U." }, { "name": "Steinbach D." }, { "name": "Quesneville H." }, { "name": "Kersey P.J." } ], "journal": "Plant Genome" } } ], "credit": [ { "name": null, "email": "urgi-contact@versailles.inra.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "cpommier", "additionDate": "2017-03-23T14:24:24Z", "lastUpdate": "2025-07-29T13:42:38.871501Z", "editPermission": { "type": "group", "authors": [ "urgi-contact", "animalandcropgenomics", "nfrancillon", "cmichotey" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BIGR XNAT", "description": "Imaging platform based on the open source XNAT software. It is used for sharing de-identified medical imaging data, and for data exchange in collaborative research projects. 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XNAT was originally developed at Washington University in the Buckner Lab, which is now located at Harvard University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data. Thanks to its extensibility, XNAT can be used to support a wide range of imaging-based projects.", "homepage": "https://xnat.org", "biotoolsID": "xnat", "biotoolsCURIE": "biotools:xnat", "version": [], "otherID": [], "relation": [ { "biotoolsID": "xnatpy", "type": "usedBy" }, { "biotoolsID": "rxnat", "type": "usedBy" }, { "biotoolsID": "xnat-pic", "type": "usedBy" }, { "biotoolsID": "bigr_xnat", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Data deposition" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3802", "term": "Data sorting" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3283", "term": "Anonymisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web API" ], "topic": [ { "uri": "http://edamontology.org/topic_3384", "term": "Medical imaging" }, { "uri": "http://edamontology.org/topic_3444", "term": "MRI" }, { "uri": "http://edamontology.org/topic_3383", "term": "Bioimaging" }, { "uri": "http://edamontology.org/topic_3452", "term": "Tomography" }, { "uri": "http://edamontology.org/topic_3071", "term": "Data management" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java" ], "license": "BSD-2-Clause", "collectionID": [ "EUCAIM" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://groups.google.com/g/xnat_discussion/", "type": [ "Discussion forum" ], "note": null }, { "url": "https://bitbucket.org/xnatdev/workspace/repositories/", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://xnat.org/download/", "type": "Downloads page", "note": null, "version": null } ], "documentation": [ { "url": "https://wiki.xnat.org/documentation/", "type": [ "User manual" ], "note": null }, { "url": "https://wiki.xnat.org/xnat-api/xnat-rest-api-directory", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1385/ni:5:1:11", "pmid": "17426351", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The extensible neuroimaging archive toolkit: An informatics platform for managing, exploring, and sharing neuroimaging data", "abstract": "The Extensible Neuroimaging Archive Toolkit (XNAT) is a software platform designed to facilitate common management and productivity tasks for neuroimaging and associated data. In particular, XNAT enables qualitycontrol procedures and provides secure access to and storage of data. XNAT follows a threetiered architecture that includes a data archive, user interface, and middleware engine. Data can be entered into the archive as XML or through data entry forms. Newly added data are stored in a virtual quarantine until an authorized user has validated it. XNAT subsequently maintains a history profile to track all changes made to the managed data. User access to the archive is provided by a secure web application. The web application provides a number of quality control and productivity features, including data entry forms, data-type-specific searches, searches that combine across data types, detailed reports, and listings of experimental data, upload/download tools, access to standard laboratory workflows, and administration and security tools. XNAT also includes an online image viewer that supports a number of common neuroimaging formats, including DICOM and Analyze. The viewer can be extended to support additional formats and to generate custom displays. By managing data with XNAT, laboratories are prepared to better maintain the long-term integrity of their data, to explore emergent relations across data types, and to share their data with the broader neuroimaging community. © Copyright 2007 by Humana Press Inc. All rights of any nature whatsoever are reserved.", "date": "2007-03-01T00:00:00Z", "citationCount": 378, "authors": [ { "name": "Marcus D.S." }, { "name": "Olsen T.R." }, { "name": "Ramaratnam M." }, { "name": "Buckner R.L." } ], "journal": "Neuroinformatics" } }, { "doi": "10.1162/jocn.2009.21407", "pmid": "19929323", "pmcid": "PMC2895005", "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "Open access series of imaging studies: Longitudinal MRI data in nondemented and demented older adults", "abstract": "The Open Access Series of Imaging Studies is a series of neuroimaging data sets that are publicly available for study and analysis. The present MRI data set consists of a longitudinal collection of 150 subjects aged 60 to 96 years all acquired on the same scanner using identical sequences. Each subject was scanned on two or more visits, separated by at least 1 year for a total of 373 imaging sessions. Subjects were characterized using the Clinical Dementia Rating (CDR) as either nondemented or with very mild tomild Alzheimer's disease. Seventy-two of the subjects were characterized as nondemented throughout the study. Sixty-four of the included subjects were characterized as demented at the time of their initial visits and remained so for subsequent scans, including 51 individuals with CDR 0.5 similar level of impairment to individuals elsewhere considered to have \"mild cognitive impairment.\" Another 14 subjects were characterized as nondemented at the time of their initial visit (CDR 0) and were subsequently characterized as demented at a later visit (CDR > 0). The subjects were all right-handed and include bothmen (n=62) and women (n = 88). For each scanning session, three or four individual T1-weighted MRI scans were obtained. Multiple withinsession acquisitions provide extremely high contrast to noise, making the data amenable to a wide range of analytic approaches including automated computational analysis. Automated calculation of whole-brain volume is presented to demonstrate use of the data for measuring differences associated with normal aging and Alzheimer's disease. © 2010 Massachusetts Institute of Technology.", "date": "2010-12-01T00:00:00Z", "citationCount": 461, "authors": [ { "name": "Marcus D.S." }, { "name": "Fotenos A.F." }, { "name": "Csernansky J.G." }, { "name": "Morris J.C." }, { "name": "Buckner R.L." } ], "journal": "Journal of Cognitive Neuroscience" } } ], "credit": [ { "name": "Daniel Marcus", "email": "dmarcus@wustl.edu", "url": "https://profiles.wustl.edu/en/persons/daniel-marcus", "orcidid": "https://orcid.org/0000-0001-5662-5358", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "hachterberg", "additionDate": "2025-07-24T08:48:17.637773Z", "lastUpdate": "2025-07-24T08:53:51.609723Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "EukCC", "description": "EukCC is a completeness and contamination estimator for metagenomic assembled microbial eukaryotic genomes.", "homepage": "https://github.com/EBI-Metagenomics/EukCC", "biotoolsID": "eukcc", "biotoolsCURIE": "biotools:eukcc", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3180", "term": "Sequence assembly validation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3494", "term": "DNA sequence" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2886", "term": "Protein sequence record" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2955", "term": "Sequence report" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" } ], "operatingSystem": [], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/s13059-020-02155-4", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Estimating the quality of eukaryotic genomes recovered from metagenomic analysis with EukCC", "abstract": "Microbial eukaryotes constitute a significant fraction of biodiversity and have recently gained more attention, but the recovery of high-quality metagenomic assembled eukaryotic genomes is limited by the current availability of tools. To help address this, we have developed EukCC, a tool for estimating the quality of eukaryotic genomes based on the automated dynamic selection of single copy marker gene sets. We demonstrate that our method outperforms current genome quality estimators, particularly for estimating contamination, and have applied EukCC to datasets derived from two different environments to enable the identification of novel eukaryote genomes, including one from the human skin.", "date": "2020-09-10T00:00:00Z", "citationCount": 70, "authors": [ { "name": "Saary P." }, { "name": "Mitchell A.L." }, { "name": "Finn R.D." } ], "journal": "Genome Biology" } } ], "credit": [], "owner": "m.bernt", "additionDate": "2025-07-24T07:14:51.692628Z", "lastUpdate": "2025-07-24T07:14:51.694965Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ETENLNC", "description": "ETENLNC (End-To-End-Novel-NonCoding) is a lncRNA identification and analysis framework", "homepage": "https://github.com/EvolOMICS-TU/ETENLNC", "biotoolsID": "etenlnc", "biotoolsCURIE": "biotools:etenlnc", "version": [ "1.0" 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"format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_0906", "term": "Protein interaction data" }, "format": [] } ], "note": "Run ETENLNC on paired-end raw RNA-Seq (.fastq) data", "cmd": "bash ETENLNC_docker.sh" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [], "license": "GPL-3.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/EvolOMICS-TU/ETENLNC", "type": [ "Repository" ], "note": "GitHub Repo" } ], "download": [ { "url": "https://zenodo.org/records/14325721?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6ImVmYTllNWJkLWE4ODUtNGM3OC05YTAxLWM4ZDk5YTljZDZjMCIsImRhdGEiOnt9LCJyYW5kb20iOiI4M2I1YjBlZDQ4MmUyZTIxNDg2YmI0YTFkMWE5MTI1OCJ9.HeB3WrsPduNzMyXjH4x5HfCgmIp4NzYv0P_11XU9lcXC_ZxEaVndP-kD0LDkxwufHVNlroeAhdK33PR51F6jnw", "type": "Biological data", "note": "Sample/demo data for ETENLNC. A detailed guide on running ETENLNC using the demo data can be found in the ETENLNC manual (supplementary to our publication).", "version": "1.0" } ], "documentation": [ { "url": "https://github.com/EvolOMICS-TU/ETENLNC", "type": [ "Command-line options" ], "note": "A detailed guide on running ETENLNC using the demo data can be found in the ETENLNC manual (supplementary to our publication)" } ], "publication": [ { "doi": "10.1016/j.compbiolchem.2024.108140", "pmid": "38996755", "pmcid": null, "type": [ "Primary" ], "version": ".0", "note": null, "metadata": { "title": "ETENLNC: An end to end lncRNA identification and analysis framework to facilitate construction of known and novel lncRNA regulatory networks", "abstract": "Long non-coding RNAs (lncRNAs) play crucial roles in the regulation of gene expression and maintenance of genomic integrity through various interactions with DNA, RNA, and proteins. The availability of large-scale sequence data from various high-throughput platforms has opened possibilities to identify, predict, and functionally annotate lncRNAs. As a result, there is a growing demand for an integrative computational framework capable of identifying known lncRNAs, predicting novel lncRNAs, and inferring the downstream regulatory interactions of lncRNAs at the genome-scale. We present ETENLNC (End-To-End-Novel-Long-NonCoding), a user-friendly, integrative, open-source, scalable, and modular computational framework for identifying and analyzing lncRNAs from raw RNA-Seq data. ETENLNC employs six stringent filtration steps to identify novel lncRNAs, performs differential expression analysis of mRNA and lncRNA transcripts, and predicts regulatory interactions between lncRNAs, mRNAs, miRNAs, and proteins. We benchmarked ETENLNC against six existing tools and optimized it for desktop workstations and high-performance computing environments using data from three different species. ETENLNC is freely available on GitHub: https://github.com/EvolOMICS-TU/ETENLNC.", "date": "2024-10-01T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Nath P." }, { "name": "Bhuyan K." }, { "name": "Bhattacharyya D.K." }, { "name": "Barah P." } ], "journal": "Computational Biology and Chemistry" } } ], "credit": [ { "name": "Pankaj Barah", "email": "barah@tezu.ernet.in", "url": "https://www.tezu.ernet.in/dmbbt/profile/34", "orcidid": "https://orcid.org/0000-0001-7039-7996", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer" ], "note": "Assistant Professor at Department of Molecular Biology and Biotechnology, Tezpur University." }, { "name": "Prangan Nath", "email": "prangannathofficial@gmai.com", "url": null, "orcidid": "https://orcid.org/0000-0002-9451-7822", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer" ], "note": null } ], "owner": "prangannath", "additionDate": "2025-07-23T10:27:57.572501Z", "lastUpdate": "2025-07-23T10:27:57.574879Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "GO FEAT", "description": "Rapid web-based functional annotation tool for genomic and transcriptomic data.", "homepage": "http://computationalbiology.ufpa.br/gofeat/", "biotoolsID": "go_feat", "biotoolsCURIE": "biotools:go_feat", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3672", "term": "Gene functional annotation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "CC-BY-4.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://computationalbiology.ufpa.br/gofeat/index/about", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1038/s41598-018-20211-9", "pmid": "29379090", "pmcid": "PMC5789007", "type": [], "version": null, "note": null, "metadata": { "title": "GO FEAT: A rapid web-based functional annotation tool for genomic and transcriptomic data", "abstract": "Downstream analysis of genomic and transcriptomic sequence data is often executed by functional annotation that can be performed by various bioinformatics tools and biological databases. However, a full fast integrated tool is not available for such analysis. Besides, the current available software is not able to produce analytic lists of annotations and graphs to help users in evaluating the output results. Therefore, we present the Gene Ontology Functional Enrichment Annotation Tool (GO FEAT), a free web platform for functional annotation and enrichment of genomic and transcriptomic data based on sequence homology search. The analysis can be customized and visualized as per users' needs and specifications. GO FEAT is freely available at http://computationalbiology.ufpa.br/gofeat/ and its source code is hosted at https://github.com/fabriciopa/gofeat.", "date": "2018-12-01T00:00:00Z", "citationCount": 78, "authors": [ { "name": "Araujo F.A." }, { "name": "Barh D." }, { "name": "Silva A." }, { "name": "Guimaraes L." }, { "name": "Ramos R.T.J." } ], "journal": "Scientific Reports" } } ], "credit": [ { "name": "Contact form", "email": null, "url": "http://computationalbiology.ufpa.br/gofeat/index/contact", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "d.gabrielaitis", "additionDate": "2018-07-09T17:41:23Z", "lastUpdate": "2025-07-21T09:32:25.390877Z", "editPermission": { "type": "group", "authors": [ "nothing2543i" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SubtiWiki", "description": "SubtiWiki is a database for the model organism Bacillus subtilis.", "homepage": "https://subtiwiki.uni-goettingen.de/", "biotoolsID": "subtiwiki", "biotoolsCURIE": "biotools:subtiwiki", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3208", "term": "Genome visualisation" }, { "uri": "http://edamontology.org/operation_0435", "term": "Operon prediction" }, { "uri": "http://edamontology.org/operation_1781", "term": "Gene regulatory network analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_3407", "term": "Endocrinology and metabolism" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkae957", "pmid": "39441067", "pmcid": "PMC11701700", "type": [ "Primary" ], "version": "5.0", "note": null, "metadata": { "title": "A new framework for SubtiWiki, the database for the model organism Bacillus subtilis", "abstract": "Bacillus subtilis is a Gram-positive model bacterium and one of the most-studied and best understood organisms. The complex information resulting from its investigation is compiled in the database SubtiWiki (https://subtiwiki.uni-goettingen.de/v5) in an integrated and intuitive manner. To enhance the utility of SubtiWiki, we have added novel features such as a viewer to interrogate conserved genomic organization, a widget that shows mutant fitness data for all non-essential genes, and a widget showing protein structures, structure predictions and complex structures. Moreover, we have integrated metabolites as new entities. The new framework also includes a documented API, enabling programmatic access to data for computational tasks. Here we present the recent developments of SubtiWiki and the current state of the data for this organism.", "date": "2025-01-06T00:00:00Z", "citationCount": 4, "authors": [ { "name": "Elfmann C." }, { "name": "Dumann V." }, { "name": "van den Berg T." }, { "name": "Stulke J." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Jörg Stülke", "email": "jstuelk@gwdg.de", "url": null, "orcidid": "https://orcid.org/0000-0001-5881-5390", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Christoph Elfmann", "email": "christoph.elfmann@uni-goettingen.de", "url": null, "orcidid": "https://orcid.org/0000-0002-7872-8232", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "PhD student in charge of SubtiWiki." } ], "owner": "ChristophElfmann", "additionDate": "2022-03-13T11:27:48.265908Z", "lastUpdate": "2025-07-16T13:05:53.746014Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "SCANPY", "description": "Scalable toolkit for analyzing single-cell gene expression data. It includes preprocessing, visualization, clustering, pseudotime and trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells.", "homepage": "https://github.com/theislab/Scanpy", "biotoolsID": "scanpy", "biotoolsCURIE": "biotools:scanpy", "version": [], "otherID": [], "relation": [ { "biotoolsID": "anndata", "type": "uses" }, { "biotoolsID": "muon", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3223", "term": "Differential gene expression analysis" }, { "uri": "http://edamontology.org/operation_2939", "term": "Principal component visualisation" }, { "uri": "http://edamontology.org/operation_0313", "term": "Expression profile clustering" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3112", "term": "Gene expression matrix" }, "format": [ { "uri": "http://edamontology.org/format_3590", "term": "HDF5" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3768", "term": "Clustered expression profiles" }, "format": [ { "uri": "http://edamontology.org/format_3590", "term": "HDF5" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_2229", "term": "Cell biology" }, { "uri": "http://edamontology.org/topic_3053", "term": "Genetics" }, { "uri": "http://edamontology.org/topic_4028", "term": "Single-cell sequencing" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Python" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/theislab/scanpy", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://scanpy.readthedocs.io/en/latest/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1186/s13059-017-1382-0", "pmid": "29409532", "pmcid": "PMC5802054", "type": [], "version": null, "note": null, "metadata": { "title": "SCANPY: Large-scale single-cell gene expression data analysis", "abstract": "Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks. Its Python-based implementation efficiently deals with data sets of more than one million cells ( https://github.com/theislab/Scanpy ). Along with Scanpy, we present AnnData, a generic class for handling annotated data matrices ( https://github.com/theislab/anndata ).", "date": "2018-02-06T00:00:00Z", "citationCount": 4146, "authors": [ { "name": "Wolf F.A." }, { "name": "Angerer P." }, { "name": "Theis F.J." } ], "journal": "Genome Biology" } } ], "credit": [ { "name": "F. Alexander Wolf", "email": "alex.wolf@helmholtz-muenchen.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "d.gabrielaitis", "additionDate": "2018-08-13T12:41:27Z", "lastUpdate": "2025-07-15T11:28:09.368913Z", "editPermission": { "type": "group", "authors": [ "pavanvidem" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "FAIR_EVA", "description": "FAIR EVA: Evaluator, Validator & Advisor has been developed to check the FAIRness level of digital objects from different repositories or data portals. It requires the object identifier (preferably persistent and unique identifier) and the repository to check. It also provides a generic and agnostic way to check digital objects.", "homepage": "https://github.com/IFCA-Advanced-Computing/FAIR_eva", "biotoolsID": "fair_eva_4_eucaim", "biotoolsCURIE": "biotools:fair_eva_4_eucaim", "version": [ "EUCAIM_plugin_1" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Web service", "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_4012", "term": "FAIR data" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [ "EUCAIM" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/IFCA-Advanced-Computing/FAIR_eva/blob/main/docs/index.md", "type": [ "Quick start guide" ], "note": "Documentation for the main package, EUCAIM plugin specific documentation not included." } ], "publication": [ { "doi": "10.1038/s41597-023-02652-8", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "FAIR EVA: Bringing institutional multidisciplinary repositories into the FAIR picture", "abstract": "The FAIR Principles are a set of good practices to improve the reproducibility and quality of data in an Open Science context. Different sets of indicators have been proposed to evaluate the FAIRness of digital objects, including datasets that are usually stored in repositories or data portals. However, indicators like those proposed by the Research Data Alliance are provided from a high-level perspective that can be interpreted and they are not always realistic to particular environments like multidisciplinary repositories. This paper describes FAIR EVA, a new tool developed within the European Open Science Cloud context that is oriented to particular data management systems like open repositories, which can be customized to a specific case in a scalable and automatic environment. It aims to be adaptive enough to work for different environments, repository software and disciplines, taking into account the flexibility of the FAIR Principles. As an example, we present DIGITAL.CSIC repository as the first target of the tool, gathering the particular needs of a multidisciplinary institution as well as its institutional repository.", "date": "2023-12-01T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Aguilar Gomez F." }, { "name": "Bernal I." } ], "journal": "Scientific Data" } } ], "credit": [ { "name": "Fernando Aguilar", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-9462-4831", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": "This software started to be developed within IFCA-Advanced-Computing receives funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 857647." } ], "owner": "davrodgon", "additionDate": "2025-06-30T08:52:48.500476Z", "lastUpdate": "2025-07-15T09:45:40.672775Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "InMoose", "description": "InMoose, the INtegrated Multi-Omic Open-Source environment, ports to Python state-of-the-art R tools for the analysis of transcriptomic data.", "homepage": "https://github.com/epigenelabs/inmoose", "biotoolsID": "inmoose", "biotoolsCURIE": "biotools:inmoose", "version": [ "0.8.0" ], "otherID": [], "relation": [ { "biotoolsID": "deseq2", "type": "isNewVersionOf" }, { "biotoolsID": "limma", "type": "isNewVersionOf" }, { "biotoolsID": "edger", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3223", "term": "Differential gene expression profiling" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3917", "term": "Count matrix" }, "format": [] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/epigenelabs/inmoose", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/epigenelabs/inmoose/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://inmoose.readthedocs.io/en/stable/", "type": [ "General" ], "note": null }, { "url": "https://colab.research.google.com/drive/1bzmNDZeaw1A6tSgfx61O6PFtaQDve6SV?usp=sharing", "type": [ "Quick start guide" ], "note": null } ], "publication": [ { "doi": "10.1038/s41598-025-03376-y", "pmid": null, "pmcid": null, "type": [ "Primary", "Usage" ], "version": null, "note": null, "metadata": { "title": "Bridging the gap between R and Python in bulk transcriptomic data analysis with InMoose", "abstract": "We introduce InMoose, an open-source Python environment aimed at omic data analysis. We illustrate its capabilities for bulk transcriptomic data analysis. Due to its wide adoption, Python has grown as a de facto standard in fields increasingly important for bioinformatic pipelines, such as data science, machine learning, or artificial intelligence (AI). As a general-purpose language, Python is also recognized for its versatility and scalability. InMoose aims at bringing state-of-the-art tools, historically written in R, to the Python ecosystem. InMoose focuses on providing drop-in replacements for R tools, to ensure consistency and reproducibility between R-based and Python-based pipelines. The first development phase has focused on bulk transcriptomic data, with current capabilities encompassing data simulation, batch effect correction, and differential analysis and meta-analysis.", "date": "2025-12-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Colange M." }, { "name": "Appe G." }, { "name": "Meunier L." }, { "name": "Weill S." }, { "name": "Johnson W.E." }, { "name": "Nordor A." }, { "name": "Behdenna A." } ], "journal": "Scientific Reports" } }, { "doi": "10.1186/s12859-023-05578-5", "pmid": null, "pmcid": null, "type": [ "Benchmarking study", "Method" ], "version": null, "note": null, "metadata": { "title": "pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods", "abstract": "Background: Variability in datasets is not only the product of biological processes: they are also the product of technical biases. ComBat and ComBat-Seq are among the most widely used tools for correcting those technical biases, called batch effects, in, respectively, microarray and RNA-Seq expression data. Results: In this technical note, we present a new Python implementation of ComBat and ComBat-Seq. While the mathematical framework is strictly the same, we show here that our implementations: (i) have similar results in terms of batch effects correction; (ii) are as fast or faster than the original implementations in R and; (iii) offer new tools for the bioinformatics community to participate in its development. pyComBat is implemented in the Python language and is distributed under GPL-3.0 (https://www.gnu.org/licenses/gpl-3.0.en.html) license as a module of the inmoose package. Source code is available at https://github.com/epigenelabs/inmoose and Python package at https://pypi.org/project/inmoose . Conclusions: We present a new Python implementation of state-of-the-art tools ComBat and ComBat-Seq for the correction of batch effects in microarray and RNA-Seq data. This new implementation, based on the same mathematical frameworks as ComBat and ComBat-Seq, offers similar power for batch effect correction, at reduced computational cost.", "date": "2023-12-01T00:00:00Z", "citationCount": 30, "authors": [ { "name": "Behdenna A." }, { "name": "Colange M." }, { "name": "Haziza J." }, { "name": "Gema A." }, { "name": "Appe G." }, { "name": "Azencott C.-A." }, { "name": "Nordor A." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1186/s12859-025-06180-7", "pmid": null, "pmcid": null, "type": [ "Benchmarking study", "Method" ], "version": null, "note": null, "metadata": { "title": "Differential expression analysis with inmoose, the integrated multi-omic open-source environment in Python", "abstract": "Background: Differential gene expression analysis is a prominent technique for the analysis of biomolecular data to identify genetic features associated with phenotypes. Limma—for microarray data –, and edgeR and DESeq2—for RNA-Seq data–, are the most widely used tools for differential gene expression analysis of bulk transcriptomic data. Results: We present the differential expression features of InMoose, a Python implementation of R tools limma, edgeR, and DESeq2. We experimentally show that InMoose stands as a drop-in replacement for those tools, with nearly identical results. This ensures reproducibility when interfacing both languages in bioinformatic pipelines. InMoose is an open source software released under the GPL3 license, available at www.github.com/epigenelabs/inmoose and https://inmoose.readthedocs.io. Conclusions: We present a new Python implementation of state-of-the-art tools limma, edgeR, and DESeq2, to perform differential gene expression analysis of bulk transcriptomic data. This new implementation exhibits results nearly identical to the original tools, improving interoperability and reproducibility between Python and R bioinformatics pipelines.", "date": "2025-12-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Colange M." }, { "name": "Appe G." }, { "name": "Meunier L." }, { "name": "Weill S." }, { "name": "Nordor A." }, { "name": "Behdenna A." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Maximilien Colange", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-4769-3302", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Epigene Labs", "email": null, "url": "https://www.epigenelabs.com/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "maximilien.colange", "additionDate": "2025-07-10T12:32:00.838316Z", "lastUpdate": "2025-07-10T13:00:37.310588Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "pyTMB", "description": "This tool was designed to calculate a Tumor Mutational Burden (TMB) score from a VCF file.", "homepage": "https://github.com/bioinfo-pf-curie/TMB?tab=readme-ov-file", "biotoolsID": "pytmb", "biotoolsCURIE": "biotools:pytmb", "version": [ "1.3.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0367", "term": "Sequence mutation and randomisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://github.com/bioinfo-pf-curie/TMB?tab=readme-ov-file", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1186/s12915-024-01839-8", "pmid": "38378561", "pmcid": "PMC10880437", "type": [], "version": null, "note": null, "metadata": { "title": "Tumor mutational burden assessment and standardized bioinformatics approach using custom NGS panels in clinical routine", "abstract": "Background: High tumor mutational burden (TMB) was reported to predict the efficacy of immune checkpoint inhibitors (ICIs). Pembrolizumab, an anti-PD-1, received FDA-approval for the treatment of unresectable/metastatic tumors with high TMB as determined by the FoundationOne®CDx test. It remains to be determined how TMB can also be calculated using other tests. Results: FFPE/frozen tumor samples from various origins were sequenced in the frame of the Institut Curie (IC) Molecular Tumor Board using an in-house next-generation sequencing (NGS) panel. A TMB calculation method was developed at IC (IC algorithm) and compared to the FoundationOne® (FO) algorithm. Using IC algorithm, an optimal 10% variant allele frequency (VAF) cut-off was established for TMB evaluation on FFPE samples, compared to 5% on frozen samples. The median TMB score for MSS/POLE WT tumors was 8.8 mut/Mb versus 45 mut/Mb for MSI/POLE-mutated tumors. When focusing on MSS/POLE WT tumor samples, the highest median TMB scores were observed in lymphoma, lung, endometrial, and cervical cancers. After biological manual curation of these cases, 21% of them could be reclassified as MSI/POLE tumors and considered as “true TMB high.” Higher TMB values were obtained using FO algorithm on FFPE samples compared to IC algorithm (40 mut/Mb [10–3927] versus 8.2 mut/Mb [2.5–897], p < 0.001). Conclusions: We herein propose a TMB calculation method and a bioinformatics tool that is customizable to different NGS panels and sample types. We were not able to retrieve TMB values from FO algorithm using our own algorithm and NGS panel.", "date": "2024-12-01T00:00:00Z", "citationCount": 8, "authors": [ { "name": "Dupain C." }, { "name": "Gutman T." }, { "name": "Girard E." }, { "name": "Kamoun C." }, { "name": "Marret G." }, { "name": "Castel-Ajgal Z." }, { "name": "Sablin M.-P." }, { "name": "Neuzillet C." }, { "name": "Borcoman E." }, { "name": "Hescot S." }, { "name": "Callens C." }, { "name": "Trabelsi-Grati O." }, { "name": "Melaabi S." }, { "name": "Vibert R." }, { "name": "Antonio S." }, { "name": "Franck C." }, { "name": "Galut M." }, { "name": "Guillou I." }, { "name": "Halladjian M." }, { "name": "Allory Y." }, { "name": "Cyrta J." }, { "name": "Romejon J." }, { "name": "Frouin E." }, { "name": "Stoppa-Lyonnet D." }, { "name": "Wong J." }, { "name": "Le Tourneau C." }, { "name": "Bieche I." }, { "name": "Servant N." }, { "name": "Kamal M." }, { "name": "Masliah-Planchon J." } ], "journal": "BMC Biology" } } ], "credit": [], "owner": "emmcauley", "additionDate": "2025-07-08T19:12:47.994999Z", "lastUpdate": "2025-07-08T19:13:10.865891Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "COPASI", "description": "Open-source software application for creating and solving mathematical models of biological processes such as metabolic networks, cell-signaling pathways, regulatory networks, infectious diseases, and many others. It includes features to define models of biological processes, simulate and analyze these models, generate analysis reports, and import/export models in SBML format.", "homepage": "http://copasi.org/", "biotoolsID": "copasi", "biotoolsCURIE": "biotools:copasi", "version": [], "otherID": [], "relation": [ { "biotoolsID": "corc", "type": "usedBy" }, { "biotoolsID": "pycotools", "type": "usedBy" }, { "biotoolsID": "biosimulations", "type": "includedIn" }, { "biotoolsID": "sbmlwebapp", "type": "usedBy" }, { "biotoolsID": "libsbml", "type": "uses" } ], "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": 2004, "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": 171, "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": 81, "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": "2025-07-07T11:17:37.638447Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SQANTI3", "description": "SQANTI3 constitutes the first module of the Functional IsoTranscriptomics (FIT) pipeline, which is an end-to-end strategy to perform isoform-level bioinformatics analyses. \n\nThe SQANTI3 tool is designed to enable quality control and filtering of long read-defined transcriptomes, which are often rich in artifacts and false-positive isoforms. \n\nTherefore, a good curation of the transcriptome is indispensable to proceed with FIT analysis and produce valid, biologically sound conclusions/hypothesis.", "homepage": "https://github.com/ConesaLab/SQANTI3", "biotoolsID": "sqanti3", "biotoolsCURIE": "biotools:sqanti3", "version": [ "5.5" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Spain" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/ConesaLab/SQANTI3", "type": [ "Repository" ], "note": "Github repository for source code access and download" } ], "download": [ { "url": "https://github.com/ConesaLab/SQANTI3/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://github.com/ConesaLab/SQANTI3/releases/download/v5.5/SQANTI3_v5.5.zip", "type": "Binaries", "note": "Version 5.5 download link from github", "version": "5.5" } ], "documentation": [ { "url": "https://github.com/ConesaLab/SQANTI3/wiki", "type": [ "General" ], "note": "SQANTI3 main documentation resource" }, { "url": "https://github.com/ConesaLab/SQANTI3/blob/master/CODE_OF_CONDUCT.md", "type": [ "Code of conduct" ], "note": null }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-Quality-Control", "type": [ "Command-line options" ], "note": "Command-line options and instructions for the QC submodule" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-filter", "type": [ "Command-line options" ], "note": "Command-line options and instructions for the filter submodule" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-rescue", "type": [ "Command-line options" ], "note": "Command-line options and instructions for the rescue submodule" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Dependencies-and-installation", "type": [ "Installation instructions" ], "note": "Instructions to install and use sqanti, either in docker or apptainer containers or in a linux system" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Tutorial:-running-SQANTI3-on-an-example-dataset", "type": [ "Quick start guide" ], "note": "Basic tutorial with examples to start using SQANTI3" }, { "url": "https://github.com/ConesaLab/SQANTI3/releases", "type": [ "Release notes" ], "note": "Changelog and release notes for every version" }, { "url": "https://github.com/ConesaLab/SQANTI3?tab=readme-ov-file#how-to-cite-sqanti3", "type": [ "Citation instructions" ], "note": "Citation instructions are on the end of the Github repository's main page" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/SQANTI3-memory-requeriments-and-paralellization", "type": [ "Other" ], "note": "Benchmarking about the resources needed to run sqanti3 with multiple cores" } ], "publication": [ { "doi": "10.1038/s41592-024-02229-2", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "5.1", "note": "Publication of SQANTI3", "metadata": { "title": "SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms", "abstract": "SQANTI3 offers a flexible tool for quality control, curation and annotation of long-read RNA sequencing data. SQANTI3 is a tool designed for the quality control, curation and annotation of long-read transcript models obtained with third-generation sequencing technologies. Leveraging its annotation framework, SQANTI3 calculates quality descriptors of transcript models, junctions and transcript ends. With this information, potential artifacts can be identified and replaced with reliable sequences. Furthermore, the integrated functional annotation feature enables subsequent functional iso-transcriptomics analyses.", "date": "2024-05-01T00:00:00Z", "citationCount": 41, "authors": [ { "name": "Pardo-Palacios F.J." }, { "name": "Arzalluz-Luque A." }, { "name": "Kondratova L." }, { "name": "Salguero P." }, { "name": "Mestre-Tomas J." }, { "name": "Amorin R." }, { "name": "Estevan-Morio E." }, { "name": "Liu T." }, { "name": "Nanni A." }, { "name": "McIntyre L." }, { "name": "Tseng E." }, { "name": "Conesa A." } ], "journal": "Nature Methods" } }, { "doi": "10.1101/gr.222976.117", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": null, "note": "Original SQANTI publication", "metadata": { "title": "SQANTI: Extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification", "abstract": "High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in well-annotated mammalian species. The advances in sequencing technology have created a need for studies and tools that can characterize these novel variants. Here, we present SQANTI, an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse transcriptome using Pacific Biosciences (PacBio) long reads and illustrate how the tool is effective in characterizing and describing the composition of the full-length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an important number of the novel transcripts are technical artifacts of the sequencing approach and that SQANTI quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated transcriptome are novel combinations of existing splice sites, resulting more frequently in novel ORFs than novel UTRs, and are enriched in both general metabolic and neural-specific functions. We show that these new transcripts have a major impact in the correct quantification of transcript levels by state-of-the-art short-read-based quantification algorithms. By comparing our iso-transcriptome with public proteomics databases, we find that alternative isoforms are elusive to proteogenomics detection. SQANTI allows the user to maximize the analytical outcome of long-read technologies by providing the tools to deliver quality-evaluated and curated full-length transcriptomes.", "date": "2018-03-01T00:00:00Z", "citationCount": 256, "authors": [ { "name": "Tardaguila M." }, { "name": "De La Fuente L." }, { "name": "Marti C." }, { "name": "Pereira C." }, { "name": "Pardo-Palacios F.J." }, { "name": "Del Risco H." }, { "name": "Ferrell M." }, { "name": "Mellado M." }, { "name": "Macchietto M." }, { "name": "Verheggen K." }, { "name": "Edelmann M." }, { "name": "Ezkurdia I." }, { "name": "Vazquez J." }, { "name": "Tress M." }, { "name": "Mortazavi A." }, { "name": "Martens L." }, { "name": "Rodriguez-Navarro S." }, { "name": "Moreno-Manzano V." }, { "name": "Conesa A." } ], "journal": "Genome Research" } } ], "credit": [ { "name": "Ana Conesa", "email": "ana.conesa@csic.es", "url": null, "orcidid": "https://orcid.org/0000-0001-9597-311X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Pablo Atienza", "email": "pablo.atienza@csic.es", "url": null, "orcidid": "https://orcid.org/0009-0002-1093-693X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": "Maintainer of SQANTI3" }, { "name": "Fabián Robledo", "email": "fabian.robledo@csic.es", "url": null, "orcidid": "https://orcid.org/0009-0005-9047-3315", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": "Maintainer of SQANTI3 and ELIXIR-related contact" } ], "owner": "Fabian-RY", "additionDate": "2025-07-07T09:04:03.787249Z", "lastUpdate": "2025-07-07T09:35:33.280160Z", "editPermission": { "type": "group", "authors": [ "Fabian-RY" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MirGeneDB", "description": "MirGeneDB is a database of manually curated microRNA genes that have been validated and annotated as initially described in Fromm et al. 2015 , Fromm et al. 2020 and Fromm et al 2022. MirGeneDB 3.0 (Clarke and Hoye et al. 2024 ) includes more than 21,000 microRNA gene entries representing more than 1,700 microRNA families from 114 metazoan species. All microRNAs can be browsed, searched and downloaded.", "homepage": "http://mirgenedb.org/", "biotoolsID": "mirgen", "biotoolsCURIE": "biotools:mirgen", "version": [ "3.0" ], "otherID": [ { "value": "doi:10.25504/FAIRsharing.QXSgvF", "type": "doi", "version": "2.0" } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_0564", "term": "Sequence visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_1869", "term": "Organism identifier" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3134", "term": "Gene transcript report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] }, { "data": { "uri": "http://edamontology.org/data_0880", "term": "RNA secondary structure" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "Data retrieval: curated miRNA. Organism identifier: a specific miRNA identifier or a species for all miRNAs for that species. Gene transcript report: with metadata and visualization. RNA secondary structure: the hairpin loop of the miRNA with bases.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3495", "term": "RNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_2012", "term": "Sequence coordinates" }, "format": [ { "uri": "http://edamontology.org/format_2305", "term": "GFF" }, { "uri": "http://edamontology.org/format_3003", "term": "BED" } ] }, { "data": { "uri": "http://edamontology.org/data_3917", "term": "Count matrix" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" }, { "uri": "http://edamontology.org/topic_3299", "term": "Evolutionary biology" }, { "uri": "http://edamontology.org/topic_3500", "term": "Zoology" }, { "uri": "http://edamontology.org/topic_2815", "term": "Human biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "CC0-1.0", "collectionID": [ "UiO tools", "ELIXIR-NO", "ELIXIR-Norway" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Norway" ], "elixirCommunity": [], "link": [ { "url": "https://elixir.no/helpdesk", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://www.mirgenedb.org/download", "type": "Biological data", "note": "Sequence downloads for 75 species", "version": "3.0" } ], "documentation": [ { "url": "https://www.mirgenedb.org/information", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkab1101", "pmid": "34850127", "pmcid": "PMC8728216", "type": [ "Primary" ], "version": "2.1", "note": null, "metadata": { "title": "MirGeneDB 2.1: Toward a complete sampling of all major animal phyla", "abstract": "We describe an update of MirGeneDB, the manually curated microRNA gene database. Adhering to uniform and consistent criteria for microRNA annotation and nomenclature, we substantially expanded MirGeneDB with 30 additional species representing previously missing metazoan phyla such as sponges, jellyfish, rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning over ∼800 million years of animal evolution, and contains a total number of 16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new phylogenetically important species, especially those relevant for the study of whole genome duplication events, and through updating evolutionary nodes of origin for many families and genes, we were able to substantially refine our nomenclature system. All changes are traceable in the specifically developed MirGeneDB version tracker. The performance of read-pages is improved and microRNA expression matrices for all tissues and species are now also downloadable. Altogether, this update represents a significant step toward a complete sampling of all major metazoan phyla, and a widely needed foundation for comparative microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.", "date": "2022-01-07T00:00:00Z", "citationCount": 95, "authors": [ { "name": "Fromm B." }, { "name": "Hoye E." }, { "name": "Domanska D." }, { "name": "Zhong X." }, { "name": "Aparicio-Puerta E." }, { "name": "Ovchinnikov V." }, { "name": "Umu S.U." }, { "name": "Chabot P.J." }, { "name": "Kang W." }, { "name": "Aslanzadeh M." }, { "name": "Tarbier M." }, { "name": "Marmol-Sanchez E." }, { "name": "Urgese G." }, { "name": "Johansen M." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Friedlander M.R." }, { "name": "Peterson K.J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkz885", "pmid": "31598695", "pmcid": "PMC6943042", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "MirGeneDB 2.0: The metazoan microRNA complement", "abstract": "Small non-coding RNAs have gained substantial attention due to their roles in animal development and human disorders. Among them, microRNAs are special because individual gene sequences are conserved across the animal kingdom. In addition, unique and mechanistically well understood features can clearly distinguish bona fide miRNAs from the myriad other small RNAs generated by cells. However, making this distinction is not a common practice and, thus, not surprisingly, the heterogeneous quality of available miRNA complements has become a major concern in microRNA research. We addressed this by extensively expanding our curated microRNA gene database-MirGeneDB-to 45 organisms, encompassing a wide phylogenetic swath of animal evolution. By consistently annotating and naming 10,899 microRNA genes in these organisms, we show that previous microRNA annotations contained not only many false positives, but surprisingly lacked >2000 bona fide microRNAs. Indeed, curated microRNA complements of closely related organisms are very similar and can be used to reconstruct ancestral miRNA repertoires. MirGeneDB represents a robust platform for microRNA-based research, providing deeper and more significant insights into the biology and evolution of miRNAs as well as biomedical and biomarker research. MirGeneDB is publicly and freely available at http://mirgenedb.org/.", "date": "2020-01-01T00:00:00Z", "citationCount": 178, "authors": [ { "name": "Fromm B." }, { "name": "Domanska D." }, { "name": "Hoye E." }, { "name": "Ovchinnikov V." }, { "name": "Kang W." }, { "name": "Aparicio-Puerta E." }, { "name": "Johansen M." }, { "name": "Flatmark K." }, { "name": "Mathelier A." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Friedlander M.R." }, { "name": "Peterson K.J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1146/annurev-genet-120213-092023", "pmid": "26473382", "pmcid": "PMC4743252", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "A Uniform System for the Annotation of Vertebrate microRNA Genes and the Evolution of the Human microRNAome", "abstract": "Although microRNAs (miRNAs) are among the most intensively studied molecules of the past 20 years, determining what is and what is not a miRNA has not been straightforward. Here, we present a uniform system for the annotation and nomenclature of miRNA genes. We show that less than a third of the 1,881 human miRBase entries, and only approximately 16% of the 7,095 metazoan miRBase entries, are robustly supported as miRNA genes. Furthermore, we show that the human repertoire of miRNAs has been shaped by periods of intense miRNA innovation and that mature gene products show a very different tempo and mode of sequence evolution than star products. We establish a new open access database-MirGeneDB (http://mirgenedb.org)-to catalog this set of miRNAs, which complements the efforts of miRBase but differs from it by annotating the mature versus star products and by imposing an evolutionary hierarchy upon this curated and consistently named repertoire.", "date": "2015-11-23T00:00:00Z", "citationCount": 435, "authors": [ { "name": "Fromm B." }, { "name": "Billipp T." }, { "name": "Peck L.E." }, { "name": "Johansen M." }, { "name": "Tarver J.E." }, { "name": "King B.L." }, { "name": "Newcomb J.M." }, { "name": "Sempere L.F." }, { "name": "Flatmark K." }, { "name": "Hovig E." }, { "name": "Peterson K.J." } ], "journal": "Annual Review of Genetics" } }, { "doi": "10.1093/nar/gkae1094", "pmid": "39673268", "pmcid": "PMC11701709", "type": [ "Primary" ], "version": "3.0", "note": null, "metadata": { "title": "MirGeneDB 3.0: Improved taxonomic sampling, uniform nomenclature of novel conserved microRNA families and updated covariance models", "abstract": "We present a major update of MirGeneDB (3.0), the manually curated animal microRNA gene database. Beyond moving to a new server and the creation of a computational mirror, we have expanded the database with the addition of 33 invertebrate species, including representatives of 5 previously unsampled phyla, and 6 mammal species. MirGeneDB now contains entries for 21 822 microRNA genes (5160 of these from the new species) belonging to 1743 microRNA families. The inclusion of these new species allowed us to refine both the evolutionary node of appearance of a number of microRNA genes/families, as well as MirGeneDB's phylogenetically informed nomenclature system. Updated covariance models of all microRNA families, along with all smallRNA read data are now downloadable. These enhanced annotations will allow researchers to analyze microRNA properties such as secondary structure and features of their biogenesis within a robust phylogenetic context and without the database plagued with numerous false positives and false negatives. In light of these improvements, MirGeneDB 3.0 will assume the responsibility for naming conserved novel metazoan microRNAs. MirGeneDB is part of RNAcentral and Elixir Norway and is publicly and freely available at mirgenedb.org.", "date": "2025-01-06T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Clarke A.W." }, { "name": "Hoye E." }, { "name": "Hembrom A.A." }, { "name": "Paynter V.M." }, { "name": "Vinther J." }, { "name": "Wyrozemski L." }, { "name": "Biryukova I." }, { "name": "Formaggioni A." }, { "name": "Ovchinnikov V." }, { "name": "Herlyn H." }, { "name": "Pierce A." }, { "name": "Wu C." }, { "name": "Aslanzadeh M." }, { "name": "Cheneby J." }, { "name": "Martinez P." }, { "name": "Friedlander M.R." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Umu S.U." }, { "name": "Johansen M." }, { "name": "Peterson K.J." }, { "name": "Fromm B." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Bastian Fromm", "email": "BastianFromm@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-0352-3037", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer", "Support" ], "note": null }, { "name": "Kevin J. Peterson", "email": "kevin.j.peterson@dartmouth.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer" ], "note": null }, { "name": "The Norwegian Bioinformatics Platform (ELIXIR-Norway) Helpdesk", "email": "support@elixir.no", "url": "https://elixir.no/helpdesk", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Support" ], "note": null }, { "name": "University of Oslo", "email": null, "url": "https://www.uio.no/english/index.html", "orcidid": null, "gridid": "grid.5510.1", "rorid": "01xtthb56", "fundrefid": "10.13039/501100005366", "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "UiO", "additionDate": "2016-02-09T13:19:44Z", "lastUpdate": "2025-07-05T22:33:30.082420Z", "editPermission": { "type": "group", "authors": [ "eca008" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "VADR", "description": "Classification and annotation of viral sequences based on RefSeq annotation.", "homepage": "https://github.com/nawrockie/vadr", "biotoolsID": "VADR", "biotoolsCURIE": "biotools:VADR", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Data deposition" }, { "uri": "http://edamontology.org/operation_0447", "term": "Sequence alignment validation" }, { "uri": "http://edamontology.org/operation_0361", "term": "Sequence annotation" }, { "uri": "http://edamontology.org/operation_0363", "term": "Reverse complement" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_0781", "term": "Virology" }, { "uri": "http://edamontology.org/topic_0623", "term": "Gene and protein families" }, { "uri": "http://edamontology.org/topic_0160", "term": "Sequence sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" } ], "operatingSystem": [], "language": [ "Perl" ], "license": null, "collectionID": [ "COVID-19" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/s12859-020-3537-3", "pmid": "32448124", "pmcid": "PMC7245624", "type": [], "version": null, "note": null, "metadata": { "title": "VADR: Validation and annotation of virus sequence submissions to GenBank", "abstract": "Background: GenBank contains over 3 million viral sequences. The National Center for Biotechnology Information (NCBI) previously made available a tool for validating and annotating influenza virus sequences that is used to check submissions to GenBank. Before this project, there was no analogous tool in use for non-influenza viral sequence submissions. Results: We developed a system called VADR (Viral Annotation DefineR) that validates and annotates viral sequences in GenBank submissions. The annotation system is based on the analysis of the input nucleotide sequence using models built from curated RefSeqs. Hidden Markov models are used to classify sequences by determining the RefSeq they are most similar to, and feature annotation from the RefSeq is mapped based on a nucleotide alignment of the full sequence to a covariance model. Predicted proteins encoded by the sequence are validated with nucleotide-to-protein alignments using BLAST. The system identifies 43 types of \"alerts\" that (unlike the previous BLAST-based system) provide deterministic and rigorous feedback to researchers who submit sequences with unexpected characteristics. VADR has been integrated into GenBank's submission processing pipeline allowing for viral submissions passing all tests to be accepted and annotated automatically, without the need for any human (GenBank indexer) intervention. Unlike the previous submission-checking system, VADR is freely available (https://github.com/nawrockie/vadr) for local installation and use. VADR has been used for Norovirus submissions since May 2018 and for Dengue virus submissions since January 2019. Since March 2020, VADR has also been used to check SARS-CoV-2 sequence submissions. Other viruses with high numbers of submissions will be added incrementally. Conclusion: VADR improves the speed with which non-flu virus submissions to GenBank can be checked and improves the content and quality of the GenBank annotations. The availability and portability of the software allow researchers to run the GenBank checks prior to submitting their viral sequences, and thereby gain confidence that their submissions will be accepted immediately without the need to correspond with GenBank staff. Reciprocally, the adoption of VADR frees GenBank staff to spend more time on services other than checking routine viral sequence submissions.", "date": "2020-05-24T00:00:00Z", "citationCount": 51, "authors": [ { "name": "Schaffer A.A." }, { "name": "Hatcher E.L." }, { "name": "Yankie L." }, { "name": "Shonkwiler L." }, { "name": "Brister J.R." }, { "name": "Karsch-Mizrachi I." }, { "name": "Nawrocki E.P." } ], "journal": "BMC Bioinformatics" } } ], "credit": [], "owner": "Pub2Tools", "additionDate": "2020-01-14T08:51:18Z", "lastUpdate": "2025-07-05T14:56:17.738501Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Pyteomics", "description": "Framework for proteomics data analysis, supporting mzML, MGF, pepXML and more.", "homepage": "https://pyteomics.readthedocs.io/", "biotoolsID": "pyteomics", "biotoolsCURIE": "biotools:pyteomics", "version": [ "4.7.5" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3767", "term": "Protein identification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_3651", "term": "MGF" }, { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [ "Proteomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/levitsky/pyteomics", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://pypi.org/project/pyteomics/", "type": "Software package", "note": null, "version": null } ], "documentation": [ { "url": "https://pyteomics.readthedocs.io/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1007/s13361-012-0516-6", "pmid": "23292976", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Pyteomics - A python framework for exploratory data analysis and rapid software prototyping in proteomics", "abstract": "Pyteomics is a cross-platform, open-source Python library providing a rich set of tools for MS-based proteomics. It provides modules for reading LC-MS/MS data, search engine output, protein sequence databases, theoretical prediction of retention times, electrochemical properties of polypeptides, mass and m/z calculations, and sequence parsing. Pyteomics is available under Apache license; release versions are available at the Python Package Index http://pypi.python. org/pyteomics, the source code repository at http://hg.theorchromo.ru/pyteomics, documentation at http://packages.python.org/pyteomics. Pyteomics.biolccc documentation is available at http://packages.python.org/pyteomics.biolccc/. Questions on installation and usage can be addressed to pyteomics mailing list: pyteomics@googlegroups.com [Figure not available: see fulltext.] © 2013 American Society for Mass Spectrometry.", "date": "2013-02-01T00:00:00Z", "citationCount": 141, "authors": [ { "name": "Goloborodko A.A." }, { "name": "Levitsky L.I." }, { "name": "Ivanov M.V." }, { "name": "Gorshkov M.V." } ], "journal": "Journal of the American Society for Mass Spectrometry" } }, { "doi": "10.1021/acs.jproteome.8b00717", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Pyteomics 4.0: Five Years of Development of a Python Proteomics Framework", "abstract": "Many of the novel ideas that drive today's proteomic technologies are focused essentially on experimental or data-processing workflows. The latter are implemented and published in a number of ways, from custom scripts and programs, to projects built using general-purpose or specialized workflow engines; a large part of routine data processing is performed manually or with custom scripts that remain unpublished. Facilitating the development of reproducible data-processing workflows becomes essential for increasing the efficiency of proteomic research. To assist in overcoming the bioinformatics challenges in the daily practice of proteomic laboratories, 5 years ago we developed and announced Pyteomics, a freely available open-source library providing Python interfaces to proteomic data. We summarize the new functionality of Pyteomics developed during the time since its introduction.", "date": "2019-02-01T00:00:00Z", "citationCount": 117, "authors": [ { "name": "Levitsky L.I." }, { "name": "Klein J.A." }, { "name": "Ivanov M.V." }, { "name": "Gorshkov M.V." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Pyteomics Google Groups", "email": "pyteomics@googlegroups.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null }, { "name": "Issue tracker", "email": null, "url": "https://github.com/levitsky/pyteomics/issues", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "msutils_import", "additionDate": "2017-01-17T14:50:32Z", "lastUpdate": "2025-07-04T15:07:26.685242Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "levitsky" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SILVA rRNA database", "description": "SILVA provides comprehensive, quality checked and regularly updated datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukaryota).", "homepage": "https://www.arb-silva.de", "biotoolsID": "silva", "biotoolsCURIE": "biotools:silva", "version": [], "otherID": [ { "value": "RRID:SCR_006423", "type": "rrid", "version": null } ], "relation": [ { "biotoolsID": "silvangs", "type": "usedBy" }, { "biotoolsID": "d3hub", "type": "includedIn" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_1868", "term": "Taxon" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_1046", "term": "Strain name" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_1088", "term": "Article ID" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_2909", "term": "Organism name" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2955", "term": "Sequence report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] }, { "data": { "uri": "http://edamontology.org/data_1383", "term": "Sequence alignment (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] }, { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] } ], "note": "The search and retrieval functions of the SILVA website can be used to build custom subsets of sequences. In addition to simple searches e.g. for accession numbers, organism names, taxonomic entities, or publication DOI/PubMed IDs, complex queries over several database fields using constraints such as sequence length or quality values are possible. The results can be sorted according to accession numbers, organism names, sequence length, sequence and alignment quality and Pintail values. The search results show accession number, organism name, sequence length, sequence quality values, taxonomic classifications, and links to view the full sequence record on SILVA and on ENA. Sequences found via search and added to download cart can be downloaded as FASTA and ARB files.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2419", "term": "Primer and probe design" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1207", "term": "nucleotide" } ] }, { "data": { "uri": "http://edamontology.org/data_1240", "term": "PCR primers" }, "format": [ { "uri": "http://edamontology.org/format_1207", "term": "nucleotide" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] }, { "data": { "uri": "http://edamontology.org/data_0850", "term": "Sequence set" }, "format": [ { "uri": "http://edamontology.org/format_2333", "term": "Binary format" } ] }, { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] }, { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] } ], "note": "The SILVA Probe Match and Evaluation Tool detects and displays all occurrences of a given probe or primer sequence in the SILVA datasets. \n\nTestPrime allows you to evaluate the performance of primer pairs by running an in silico PCR on the SILVA databases. From the results of the PCR, TestPrime computes coverages for each taxonomic group in all of the taxonomies offered by SILVA.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0492", "term": "Multiple sequence alignment" }, { "uri": "http://edamontology.org/operation_0496", "term": "Global alignment" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" }, { "uri": "http://edamontology.org/operation_0547", "term": "Phylogenetic inference (maximum likelihood and Bayesian methods)" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] }, { "data": { "uri": "http://edamontology.org/data_0867", "term": "Sequence alignment report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_0872", "term": "Phylogenetic tree" }, "format": [ { "uri": "http://edamontology.org/format_1910", "term": "newick" } ] }, { "data": { "uri": "http://edamontology.org/data_1872", "term": "Taxonomic classification" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": "The Alignment, Classification and Tree Service (ACT) of SILVA allows to align and optionally classify sequences using the SILVA Incremental Aligner (SINA). From aligned sequences, (optionally) phylogenetic trees can be inferred using FastTree or RAxML.", "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" }, { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_3050", "term": "Biodiversity" }, { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" }, { "uri": "http://edamontology.org/topic_0632", "term": "Probes and primers" } ], "operatingSystem": [], "language": [], "license": "CC-BY-4.0", "collectionID": [ "de.NBI", "de.NBI-biodata", "DSMZ Digital Diversity" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data" ], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://www.arb-silva.de/browser/", "type": [ "Service" ], "note": "SILVA Taxonomy Browser" }, { "url": "https://www.arb-silva.de/search/", "type": [ "Service" ], "note": "SILVA metadata search" }, { "url": "https://www.arb-silva.de/aligner/", "type": [ "Service" ], "note": "ACT: Alignment, Classification and Tree Service" }, { "url": "https://www.arb-silva.de/search/testprobe/", "type": [ "Service" ], "note": "SILVA Probe Match and Evaluation Tool" }, { "url": "https://www.arb-silva.de/search/testprime/", "type": [ "Service" ], "note": "SILVA Primer Evaluation Tool" }, { "url": "https://treeviewer.arb-silva.de/", "type": [ "Service" ], "note": "Web-based viewer for the SILVA guide trees" } ], "download": [ { "url": "https://www.arb-silva.de/download/archive/", "type": "Downloads page", "note": "SILVA dataset archive", "version": null } ], "documentation": [ { "url": "https://www.arb-silva.de/silva-license-information/", "type": [ "Terms of use" ], "note": null }, { "url": "https://www.arb-silva.de/contact/", "type": [ "Citation instructions" ], "note": null }, { "url": "https://www.arb-silva.de/documentation/", "type": [ "General" ], "note": null }, { "url": "https://www.arb-silva.de/documentation/faqs/", "type": [ "FAQ" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gks1219", "pmid": "23193283", "pmcid": "PMC3531112", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3194 778 small subunit and 288717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches. © The Author(s) 2012.", "date": "2013-01-01T00:00:00Z", "citationCount": 22633, "authors": [ { "name": "Quast C." }, { "name": "Pruesse E." }, { "name": "Yilmaz P." }, { "name": "Gerken J." }, { "name": "Schweer T." }, { "name": "Yarza P." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkt1209", "pmid": "24293649", "pmcid": "PMC3965112", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "The SILVA and \"all-species Living Tree Project (LTP)\" taxonomic frameworks", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive resource for up-to-date quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. SILVA provides a manually curated taxonomy for all three domains of life, based on representative phylogenetic trees for the small- and large-subunit rRNA genes. This article describes the improvements the SILVA taxonomy has undergone in the last 3 years. Specifically we are focusing on the curation process, the various resources used for curation and the comparison of the SILVA taxonomy with Greengenes and RDP-II taxonomies. Our comparisons not only revealed a reasonable overlap between the taxa names, but also points to significant differences in both names and numbers of taxa between the three resources. © 2013 The Author(s). Published by Oxford University Press.", "date": "2014-01-01T00:00:00Z", "citationCount": 2590, "authors": [ { "name": "Yilmaz P." }, { "name": "Parfrey L.W." }, { "name": "Yarza P." }, { "name": "Gerken J." }, { "name": "Pruesse E." }, { "name": "Quast C." }, { "name": "Schweer T." }, { "name": "Peplies J." }, { "name": "Ludwig W." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkm864", "pmid": "17947321", "pmcid": "PMC2175337", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB", "abstract": "Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs. © 2007 The Author(s).", "date": "2007-12-01T00:00:00Z", "citationCount": 5291, "authors": [ { "name": "Pruesse E." }, { "name": "Quast C." }, { "name": "Knittel K." }, { "name": "Fuchs B.M." }, { "name": "Ludwig W." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/bts252", "pmid": "22556368", "pmcid": "PMC3389763", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes", "abstract": "Motivation: In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements.Results: In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. © The Author(s) 2012. Published by Oxford University Press.", "date": "2012-07-01T00:00:00Z", "citationCount": 2408, "authors": [ { "name": "Pruesse E." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Bioinformatics" } }, { "doi": "10.1016/j.jbiotec.2017.06.1198", "pmid": "28648396", "pmcid": null, "type": [ "Review" ], "version": null, "note": null, "metadata": { "title": "25 years of serving the community with ribosomal RNA gene reference databases and tools", "abstract": "SILVA (lat. forest) is a comprehensive web resource, providing services around up to date, high-quality datasets of aligned ribosomal RNA gene (rDNA) sequences from the Bacteria, Archaea, and Eukaryota domains. SILVA dates back to the year 1991 when Dr. Wolfgang Ludwig from the Technical University Munich started the integrated software workbench ARB (lat. tree) to support high-quality phylogenetic inference and taxonomy based on the SSU and LSU rDNA marker genes. At that time, the ARB project maintained both, the sequence reference datasets and the software package for data analysis. In 2005, with the massive increase of DNA sequence data, the maintenance of the software system ARB and the corresponding rRNA databases SILVA was split between Munich and the Microbial Genomics and Bioinformatics Research Group in Bremen. ARB has been continuously developed to include new features and improve the usability of the workbench. Thousands of users worldwide appreciate the seamless integration of common analysis tools under a central graphical user interface, in combination with its versatility. The first SILVA release was deployed in February 2007 based on the EMBL-EBI/ENA release 89. Since then, full SILVA releases offering the database content in various flavours are published at least annually, complemented by intermediate web-releases where only the SILVA web dataset is updated. SILVA is the only rDNA database project worldwide where special emphasis is given to the consistent naming of clades of uncultivated (environmental) sequences, where no validly described cultivated representatives are available. Also exclusive for SILVA is the maintenance of both comprehensive aligned 16S/18S rDNA and 23S/28S rDNA sequence datasets. Furthermore, the SILVA alignments and trees were designed to include Eukaryota, another unique feature among rDNA databases. With the termination of the European Ribosomal RNA Database Project in 2007, the SILVA database has become the authoritative rDNA database project for Europe. The application spectrum of ARB and SILVA ranges from biodiversity analysis, medical diagnostics, to biotechnology and quality control for academia and industry.", "date": "2017-11-10T00:00:00Z", "citationCount": 635, "authors": [ { "name": "Glockner F.O." }, { "name": "Yilmaz P." }, { "name": "Quast C." }, { "name": "Gerken J." }, { "name": "Beccati A." }, { "name": "Ciuprina A." }, { "name": "Bruns G." }, { "name": "Yarza P." }, { "name": "Peplies J." }, { "name": "Westram R." }, { "name": "Ludwig W." } ], "journal": "Journal of Biotechnology" } }, { "doi": "10.1186/s12859-017-1841-3", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SILVA tree viewer: Interactive web browsing of the SILVA phylogenetic guide trees", "abstract": "Background: Phylogenetic trees are an important tool to study the evolutionary relationships among organisms. The huge amount of available taxa poses difficulties in their interactive visualization. This hampers the interaction with the users to provide feedback for the further improvement of the taxonomic framework. Results: The SILVA Tree Viewer is a web application designed for visualizing large phylogenetic trees without requiring the download of any software tool or data files. The SILVA Tree Viewer is based on Web Geographic Information Systems (Web-GIS) technology with a PostgreSQL backend. It enables zoom and pan functionalities similar to Google Maps. The SILVA Tree Viewer enables access to two phylogenetic (guide) trees provided by the SILVA database: the SSU Ref NR99 inferred from high-quality, full-length small subunit sequences, clustered at 99% sequence identity and the LSU Ref inferred from high-quality, full-length large subunit sequences. Conclusions: The Tree Viewer provides tree navigation, search and browse tools as well as an interactive feedback system to collect any kinds of requests ranging from taxonomy to data curation and improving the tool itself.", "date": "2017-09-30T00:00:00Z", "citationCount": 29, "authors": [ { "name": "Beccati A." }, { "name": "Gerken J." }, { "name": "Quast C." }, { "name": "Yilmaz P." }, { "name": "Glockner F.O." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures", "email": "hub@dsmz.de", "url": "https://www.dsmz.de", "orcidid": null, "gridid": "grid.420081.f", "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "SILVA Team", "email": "contact@arb-silva.de", "url": "https://www.arb-silva.de/contact/team/", "orcidid": null, "gridid": "grid.507782.f", "rorid": "027z9pz32", "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "silva", "additionDate": "2016-09-30T15:59:05Z", "lastUpdate": "2025-06-30T13:26:42.882897Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "The MINERVA Platform", "description": "The MINERVA (Molecular Interaction NEtwoRk VisuAlization) platform is a standalone webserver for visualization, exploration and management of molecular networks encoded in SBGN-compliant format, including files produced using CellDesigner or SBGN editors. Visualization of uploaded networks generated by the platform is accessible via a web browser to all viewers with the weblink to the resource.\n\nThe MINERVA Platform is a webservice using the Java Server Faces 2 technology. The server side, including data parsing, integration, annotation and verification, is implemented in Java. The platform uses the Postgres SQL database for data storage and the Hibernate framework as a middle layer between web server and database. The user web-interface is generated using React.js. The displayed content is visualized by OpenLayers API, dedicated JavaScript and CSS.", "homepage": "https://minerva.uni.lu", "biotoolsID": "MINERVA_Platform", "biotoolsCURIE": "biotools:MINERVA_Platform", "version": [ "13.1.3", "13.2.0", "14.0.13", "15.0.3", "16.4.0", "17.1.3", "18.1.1" ], "otherID": [], "relation": [ { "biotoolsID": "pathvisio", "type": "uses" }, { "biotoolsID": "sbgn", "type": "uses" }, { "biotoolsID": "libsbml", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3926", "term": "Pathway visualisation" } ], "input": [], "output": [], "note": "Visualise systems biology diagrams online, on a standalone web server", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0571", "term": "Expression data visualisation" } ], "input": [], "output": [], "note": "Visualise omics data from multiple datasets on top of the diagrams", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3434", "term": "Conversion" } ], "input": [], "output": [], "note": "Convert between main systems biology layout formats: CellDeslgners SBML, SBML layout+render, SBGN-ML, GPML", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "input": [], "output": [], "note": "Use MINERVA API to access systems biology formats for modelling", "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_3391", "term": "Omics" }, { "uri": "http://edamontology.org/topic_3342", "term": "Translational medicine" }, { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" } ], "operatingSystem": [], "language": [], "license": "AGPL-3.0", "collectionID": [ "ELIXIR-LU", "LCSB" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Luxembourg" ], "elixirCommunity": [], "link": [ { "url": "https://gitlab.lcsb.uni.lu/minerva/core/", "type": [ "Repository" ], "note": "GiLab repository for core functionalities (data and format handling, service stability, API access)" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/core/-/issues", "type": [ "Issue tracker" ], "note": "Issue tracker for core functionalities (data and format handling, service stability, API access)" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/frontend", "type": [ "Repository" ], "note": "GiLab repository for frontend functionalities" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/frontend/-/issues", "type": [ "Issue tracker" ], "note": "Issue tracker for frontend functionalities" } ], "download": [ { "url": "https://minerva.pages.uni.lu/doc/install/", "type": "Other", "note": "Installation instructions, including debian package, virtual machine images and docker containers.", "version": "13.1.3 - 18.1.1" } ], "documentation": [ { "url": "https://minerva.uni.lu", "type": [ "Quick start guide", "Release notes", "User manual", "API documentation", "Citation instructions", "Terms of use" ], "note": null } ], "publication": [ { "doi": "10.1038/npjsba.2016.20", "pmid": "28725475", "pmcid": "PMC5516855", "type": [ "Primary" ], "version": "10.0", "note": null, "metadata": { "title": "MINERVA—A platform for visualization and curation of molecular interaction networks", "abstract": "Our growing knowledge about various molecular mechanisms is becoming increasingly more structured and accessible. Different repositories of molecular interactions and available literature enable construction of focused and high-quality molecular interaction networks. Novel tools for curation and exploration of such networks are needed, in order to foster the development of a systems biology environment. In particular, solutions for visualization, annotation and data cross-linking will facilitate usage of network-encoded knowledge in biomedical research. To this end we developed the MINERVA (Molecular Interaction NEtwoRks VisuAlization) platform, a standalone webservice supporting curation, annotation and visualization of molecular interaction networks in Systems Biology Graphical Notation (SBGN)-compliant format. MINERVA provides automated content annotation and verification for improved quality control. The end users can explore and interact with hosted networks, and provide direct feedback to content curators. MINERVA enables mapping drug targets or overlaying experimental data on the visualized networks. Extensive export functions enable downloading areas of the visualized networks as SBGN-compliant models for efficient reuse of hosted networks. The software is available under Affero GPL 3.0 as a Virtual Machine snapshot, Debian package and Docker instance at http://r3lab.uni.lu/web/minerva-website/. We believe that MINERVA is an important contribution to systems biology community, as its architecture enables set-up of locally or globally accessible SBGN-oriented repositories of molecular interaction networks. Its functionalities allow overlay of multiple information layers, facilitating exploration of content and interpretation of data. Moreover, annotation and verification workflows of MINERVA improve the efficiency of curation of networks, allowing life-science researchers to better engage in development and use of biomedical knowledge repositories.", "date": "2016-01-01T00:00:00Z", "citationCount": 65, "authors": [ { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Satagopam V." }, { "name": "Gebel S." }, { "name": "Mazein A." }, { "name": "Kuzma M." }, { "name": "Zorzan S." }, { "name": "McGee F." }, { "name": "Otjacques B." }, { "name": "Balling R." }, { "name": "Schneider R." } ], "journal": "npj Systems Biology and Applications" } }, { "doi": "10.1093/bioinformatics/btz286", "pmid": "31074494", "pmcid": "PMC6821317", "type": [ "Primary" ], "version": "12.2.3", "note": null, "metadata": { "title": "MINERVA API and plugins: Opening molecular network analysis and visualization to the community", "abstract": "Summary: The complexity of molecular networks makes them difficult to navigate and interpret, creating a need for specialized software. MINERVA is a web platform for visualization, exploration and management of molecular networks. Here, we introduce an extension to MINERVA architecture that greatly facilitates the access and use of the stored molecular network data. It allows to incorporate such data in analytical pipelines via a programmatic access interface, and to extend the platform's visual exploration and analytics functionality via plugin architecture. This is possible for any molecular network hosted by the MINERVA platform encoded in well-recognized systems biology formats. To showcase the possibilities of the plugin architecture, we have developed several plugins extending the MINERVA core functionalities. In the article, we demonstrate the plugins for interactive tree traversal of molecular networks, for enrichment analysis and for mapping and visualization of known disease variants or known adverse drug reactions to molecules in the network. Availability and implementation: Plugins developed and maintained by the MINERVA team are available under the AGPL v3 license at https://git-r3lab.uni.lu/minerva/plugins/. The MINERVA API and plugin documentation is available at https://minerva-web.lcsb.uni.lu.", "date": "2019-11-01T00:00:00Z", "citationCount": 25, "authors": [ { "name": "Hoksza D." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Smula E." }, { "name": "Schneider R." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bib/bbz067", "pmid": "31273380", "pmcid": "PMC7373180", "type": [ "Primary" ], "version": "13.1.1", "note": null, "metadata": { "title": "Closing the gap between formats for storing layout information in systems biology", "abstract": "The understanding of complex biological networks often relies on both a dedicated layout and a topology. Currently, there are three major competing layout-aware systems biology formats, but there are no software tools or software libraries supporting all of them. This complicates the management of molecular network layouts and hinders their reuse and extension. In this paper, we present a high-level overview of the layout formats in systems biology, focusing on their commonalities and differences, review their support in existing software tools, libraries and repositories and finally introduce a new conversion module within the MINERVA platform. The module is available via a REST API and offers, besides the ability to convert between layout-aware systems biology formats, the possibility to export layouts into several graphical formats. The module enables conversion of very large networks with thousands of elements, such as disease maps or metabolic reconstructions, rendering it widely applicable in systems biology.", "date": "2019-07-10T00:00:00Z", "citationCount": 17, "authors": [ { "name": "Hoksza D." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Hasenauer J." }, { "name": "Schneider R." } ], "journal": "Briefings in Bioinformatics" } }, { "doi": "10.1089/big.2015.0057", "pmid": "27441714", "pmcid": "PMC4932659", "type": [ "Usage" ], "version": "10.0", "note": null, "metadata": { "title": "Integration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases", "abstract": "Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services - tranSMART, a Galaxy Server, and a MINERVA platform - are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and disease-related mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data.", "date": "2016-06-01T00:00:00Z", "citationCount": 39, "authors": [ { "name": "Satagopam V." }, { "name": "Gu W." }, { "name": "Eifes S." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Gebel S." }, { "name": "Barbosa-Silva A." }, { "name": "Balling R." }, { "name": "Schneider R." } ], "journal": "Big Data" } }, { "doi": "10.1016/j.envpol.2019.04.005", "pmid": "30991279", "pmcid": null, "type": [], "version": "13.1.1", "note": null, "metadata": { "title": "Genes associated with Parkinson's disease respond to increasing polychlorinated biphenyl levels in the blood of healthy females", "abstract": "Polychlorinated biphenyls (PCBs) are a class of widespread environmental pollutants, commonly found in human blood, that have been suggested to be linked to the occurrence of sporadic Parkinson's disease (PD). It has been reported that some non-coplanar PCBs accumulate in the brains of female PD patients. To improve our understanding of the association between PCB exposure and PD risk we have applied whole transcriptome gene expression analysis in blood cells from 594 PCB-exposed subjects (369 female, 225 male). Interestingly, we observe that in females, blood levels of non-coplanar PCBs appear to be associated with expression levels of PD-specific genes. However, no such association was detected in males. Among the 131 PD-specific genes affected, 39 have been shown to display similar changes in expression levels in the substantia nigra of deceased PD patients. Especially among the down-regulated genes, transcripts of genes involved in neurotransmitter vesicle-related functions were predominant. Capsule: Plasma PCB levels are associated with gene expression changes in females only, resulting in brain-related genes changing in blood cells of healthy individuals exposed to PCBs.", "date": "2019-07-01T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Bohler S." }, { "name": "Krauskopf J." }, { "name": "Espin-Perez A." }, { "name": "Gebel S." }, { "name": "Palli D." }, { "name": "Rantakokko P." }, { "name": "Kiviranta H." }, { "name": "Kyrtopoulos S.A." }, { "name": "Balling R." }, { "name": "Kleinjans J." } ], "journal": "Environmental Pollution" } } ], "credit": [], "owner": "mjostaszewski", "additionDate": "2019-08-26T14:34:55Z", "lastUpdate": "2025-06-26T13:15:59.673112Z", "editPermission": { "type": "group", "authors": [ "sascha.herzinger" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "CoreProfiler", "description": "CoreProfiler is a cgMLST (core genome multilocus sequence typing) software that identifies alleles in bacterial genome assemblies by comparing them to a reference allele scheme. It detects both exact matches to known alleles and potential novel alleles using a two-step BLAST-based approach, enabling robust and reproducible strain genotyping.", "homepage": "https://gitlab.com/ifb-elixirfr/abromics/coreprofiler", "biotoolsID": "coreprofiler", "biotoolsCURIE": "biotools:coreprofiler", "version": [ "1.1.1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3840", "term": "Multilocus sequence typing" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://gitlab.com/ifb-elixirfr/abromics/coreprofiler/-/blob/main/README.md?ref_type=heads", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.5281/ZENODO.8282656", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null }, { "doi": "10.1016/S0022-2836(05)80360-2", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Basic local alignment search tool", "abstract": "A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straight-forward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity. © 1990, Academic Press Limited. All rights reserved.", "date": "1990-01-01T00:00:00Z", "citationCount": 80157, "authors": [ { "name": "Altschul S.F." }, { "name": "Gish W." }, { "name": "Miller W." }, { "name": "Myers E.W." }, { "name": "Lipman D.J." } ], "journal": "Journal of Molecular Biology" } } ], "credit": [], "owner": "clsiguret", "additionDate": "2025-04-08T08:17:22.895529Z", "lastUpdate": "2025-06-25T07:31:27.919999Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DeepSig", "description": "Prediction of secretory signal peptides in protein sequences", "homepage": "https://busca.biocomp.unibo.it/deepsig/", "biotoolsID": "deepsig", "biotoolsCURIE": "biotools:deepsig", "version": [ "1.2.5" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0418", "term": "Protein signal peptide detection" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_3510", "term": "Protein sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0123", "term": "Protein properties" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python", "C++" ], "license": "GPL-3.0", "collectionID": [ "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/BolognaBiocomp/deepsig", "type": "Source code", "note": null, "version": "1.2.5" }, { "url": "https://hub.docker.com/r/bolognabiocomp/deepsig", "type": "Container file", "note": null, "version": "1.2.5" } ], "documentation": [ { "url": "https://github.com/BolognaBiocomp/deepsig", "type": [ "Command-line options" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btx818", "pmid": "29280997", "pmcid": "PMC5946842", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "DeepSig: Deep learning improves signal peptide detection in proteins", "abstract": "Motivation The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Results Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. Availability and implementation DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website.", "date": "2018-05-15T00:00:00Z", "citationCount": 96, "authors": [ { "name": "Savojardo C." }, { "name": "Martelli P.L." }, { "name": "Fariselli P." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "http://biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact" ], "note": null }, { "name": "Pier Luigi Martelli", "email": "pierluigi.martelli@unibo.it", "url": "http://biocomp.unibo.it", "orcidid": "https://orcid.org/0000-0002-0274-5669", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2018-05-28T14:50:09Z", "lastUpdate": "2025-06-19T11:55:09.017105Z", "editPermission": { "type": "group", "authors": [ "savo", "ELIXIR-ITA-BOLOGNA" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "QIIME 2", "description": "QIIME 2 is an AI-ready microbiome multi-omics data science platform that is trusted, free, open source, extensible, and community developed and supported bioinformatics.", "homepage": "https://qiime2.org", "biotoolsID": "qiime2", "biotoolsCURIE": "biotools:qiime2", "version": [ "2.0" ], "otherID": [], "relation": [ { "biotoolsID": "qiime", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3933", "term": "Demultiplexing" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Suite", "Command-line tool", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" }, { "uri": "http://edamontology.org/topic_3941", "term": "Metatranscriptomics" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [ "Galaxy" ], "link": [ { "url": "https://github.com/qiime2", "type": [ "Repository" ], "note": null }, { "url": "https://library.qiime2.org", "type": [ "Software catalogue" ], "note": null }, { "url": "https://forum.qiime2.org", "type": [ "Discussion forum" ], "note": null }, { "url": "https://view.qiime2.org", "type": [ "Other" ], "note": "Site for viewing and interacting with QIIME 2 results." } ], "download": [], "documentation": [ { "url": "https://amplicon-docs.qiime2.org", "type": [ "General" ], "note": "User documentation for amplicon analysis, oriented to new users." }, { "url": "https://moshpit.qiime2.org", "type": [ "Installation instructions" ], "note": "User documentation for metagenome analysis, oriented to new users." }, { "url": "https://use.qiime2.org", "type": [ "User manual" ], "note": "User documentation, oriented toward power users." }, { "url": "https://develop.qiime2.org", "type": [ "API documentation" ], "note": "Developer documentation, including a plugin development tutorial." }, { "url": "https://library.qiime2.org/books", "type": [ "Other" ], "note": "The QIIME 2 Library Stacks: a resource for discovering relevant documentation." } ], "publication": [ { "doi": "10.1038/s41587-019-0209-9", "pmid": "31341288", "pmcid": "PMC7015180", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2", "abstract": "", "date": "2019-08-01T00:00:00Z", "citationCount": 14289, "authors": [ { "name": "Bolyen E." }, { "name": "Rideout J.R." }, { "name": "Dillon M.R." }, { "name": "Bokulich N.A." }, { "name": "Abnet C.C." }, { "name": "Al-Ghalith G.A." }, { "name": "Alexander H." }, { "name": "Alm E.J." }, { "name": "Arumugam M." }, { "name": "Asnicar F." }, { "name": "Bai Y." }, { "name": "Bisanz J.E." }, { "name": "Bittinger K." }, { "name": "Brejnrod A." }, { "name": "Brislawn C.J." }, { "name": "Brown C.T." }, { "name": "Callahan B.J." }, { "name": "Caraballo-Rodriguez A.M." }, { "name": "Chase J." }, { "name": "Cope E.K." }, { "name": "Da Silva R." }, { "name": "Diener C." }, { "name": "Dorrestein P.C." }, { "name": "Douglas G.M." }, { "name": "Durall D.M." }, { "name": "Duvallet C." }, { "name": "Edwardson C.F." }, { "name": "Ernst M." }, { "name": "Estaki M." }, { "name": "Fouquier J." }, { "name": "Gauglitz J.M." }, { "name": "Gibbons S.M." }, { "name": "Gibson D.L." }, { "name": "Gonzalez A." }, { "name": "Gorlick K." }, { "name": "Guo J." }, { "name": "Hillmann B." }, { "name": "Holmes S." }, { "name": "Holste H." }, { "name": "Huttenhower C." }, { "name": "Huttley G.A." }, { "name": "Janssen S." }, { "name": "Jarmusch A.K." }, { "name": "Jiang L." }, { "name": "Kaehler B.D." }, { "name": "Kang K.B." }, { "name": "Keefe C.R." }, { "name": "Keim P." }, { "name": "Kelley S.T." }, { "name": "Knights D." }, { "name": "Koester I." }, { "name": "Kosciolek T." }, { "name": "Kreps J." }, { "name": "Langille M.G.I." }, { "name": "Lee J." }, { "name": "Ley R." }, { "name": "Liu Y.-X." }, { "name": "Loftfield E." }, { "name": "Lozupone C." }, { "name": "Maher M." }, { "name": "Marotz C." }, { "name": "Martin B.D." }, { "name": "McDonald D." }, { "name": "McIver L.J." }, { "name": "Melnik A.V." }, { "name": "Metcalf J.L." }, { "name": "Morgan S.C." }, { "name": "Morton J.T." }, { "name": "Naimey A.T." }, { "name": "Navas-Molina J.A." }, { "name": "Nothias L.F." }, { "name": "Orchanian S.B." }, { "name": "Pearson T." }, { "name": "Peoples S.L." }, { "name": "Petras D." }, { "name": "Preuss M.L." }, { "name": "Pruesse E." }, { "name": "Rasmussen L.B." }, { "name": "Rivers A." }, { "name": "Robeson M.S." }, { "name": "Rosenthal P." }, { "name": "Segata N." }, { "name": "Shaffer M." }, { "name": "Shiffer A." }, { "name": "Sinha R." }, { "name": "Song S.J." }, { "name": "Spear J.R." }, { "name": "Swafford A.D." }, { "name": "Thompson L.R." }, { "name": "Torres P.J." }, { "name": "Trinh P." }, { "name": "Tripathi A." }, { "name": "Turnbaugh P.J." }, { "name": "Ul-Hasan S." }, { "name": "van der Hooft J.J.J." }, { "name": "Vargas F." }, { "name": "Vazquez-Baeza Y." }, { "name": "Vogtmann E." }, { "name": "von Hippel M." }, { "name": "Walters W." }, { "name": "Wan Y." }, { "name": "Wang M." }, { "name": "Warren J." }, { "name": "Weber K.C." }, { "name": "Williamson C.H.D." }, { "name": "Willis A.D." }, { "name": "Xu Z.Z." }, { "name": "Zaneveld J.R." }, { "name": "Zhang Y." }, { "name": "Zhu Q." }, { "name": "Knight R." }, { "name": "Caporaso J.G." } ], "journal": "Nature Biotechnology" } } ], "credit": [ { "name": "Greg Caporaso", "email": "greg.caporaso@nau.edu", "url": "https://cap-lab.bio", "orcidid": "https://orcid.org/0000-0002-8865-1670", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact" ], "note": null } ], "owner": "gregcaporaso", "additionDate": "2021-05-27T09:02:10Z", "lastUpdate": "2025-06-18T21:00:46.185472Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Flye", "description": "Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs.", "homepage": "https://github.com/fenderglass/Flye", "biotoolsID": "Flye", "biotoolsCURIE": "biotools:Flye", "version": [ "2.9.6" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0525", "term": "Genome assembly" }, { "uri": "http://edamontology.org/operation_0524", "term": "De-novo assembly" }, { "uri": "http://edamontology.org/operation_0523", "term": "Mapping assembly" }, { "uri": "http://edamontology.org/operation_3730", "term": "Cross-assembly" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3673", "term": "Whole genome sequencing" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "C++", "Python", "C" ], "license": "BSD-3-Clause", "collectionID": [ "ONTeater" ], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/fenderglass/Flye/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/mikolmogorov/Flye", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1099/mgen.0.000294", "pmid": "31483244", "pmcid": "PMC6807382", "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "Comparison of long-read sequencing technologies in the hybrid assembly of complex bacterial genomes", "abstract": "Illumina sequencing allows rapid, cheap and accurate whole genome bacterial analyses, but short reads (<300 bp) do not usually enable complete genome assembly. Long-read sequencing greatly assists with resolving complex bacterial genomes, particularly when combined with short-read Illumina data (hybrid assembly). However, it is not clear how different long-read sequencing methods affect hybrid assembly accuracy. Relative automation of the assembly process is also crucial to facilitating high-throughput complete bacterial genome reconstruction, avoiding multiple bespoke filtering and data manipulation steps. In this study, we compared hybrid assemblies for 20 bacterial isolates, including two reference strains, using Illumina sequencing and long reads from either Oxford Nanopore Technologies (ONT) or SMRT Pacific Biosciences (PacBio) sequencing platforms. We chose isolates from the family Enterobacteriaceae, as these frequently have highly plastic, repetitive genetic structures, and complete genome reconstruction for these species is relevant for a precise understanding of the epidemiology of antimicrobial resistance. We de novo assembled genomes using the hybrid assembler Unicycler and compared different read processing strategies, as well as comparing to long-read-only assembly with Flye followed by short-read polishing with Pilon. Hybrid assembly with either PacBio or ONT reads facilitated high-quality genome reconstruction, and was superior to the longread assembly and polishing approach evaluated with respect to accuracy and completeness. Combining ONT and Illumina reads fully resolved most genomes without additional manual steps, and at a lower consumables cost per isolate in our setting. Automated hybrid assembly is a powerful tool for complete and accurate bacterial genome assembly.", "date": "2019-01-01T00:00:00Z", "citationCount": 166, "authors": [ { "name": "De Maio N." }, { "name": "Shaw L.P." }, { "name": "Hubbard A." }, { "name": "George S." }, { "name": "Sanderson N.D." }, { "name": "Swann J." }, { "name": "Wick R." }, { "name": "Oun M.A." }, { "name": "Stubberfield E." }, { "name": "Hoosdally S.J." }, { "name": "Crook D.W." }, { "name": "Peto T.E.A." }, { "name": "Sheppard A.E." }, { "name": "Bailey M.J." }, { "name": "Read D.S." }, { "name": "Anjum M.F." }, { "name": "Sarah Walker A." }, { "name": "Stoesser N." } ], "journal": "Microbial Genomics" } }, { "doi": "10.1038/s41587-019-0072-8", "pmid": "30936562", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Assembly of long, error-prone reads using repeat graphs", "abstract": "Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers.", "date": "2019-05-01T00:00:00Z", "citationCount": 3077, "authors": [ { "name": "Kolmogorov M." }, { "name": "Yuan J." }, { "name": "Lin Y." }, { "name": "Pevzner P.A." } ], "journal": "Nature Biotechnology" } }, { "doi": "10.1038/s41592-020-00971-x", "pmid": "33020656", "pmcid": "PMC10699202", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "metaFlye: scalable long-read metagenome assembly using repeat graphs", "abstract": "Long-read sequencing technologies have substantially improved the assemblies of many isolate bacterial genomes as compared to fragmented short-read assemblies. However, assembling complex metagenomic datasets remains difficult even for state-of-the-art long-read assemblers. Here we present metaFlye, which addresses important long-read metagenomic assembly challenges, such as uneven bacterial composition and intra-species heterogeneity. First, we benchmarked metaFlye using simulated and mock bacterial communities and show that it consistently produces assemblies with better completeness and contiguity than state-of-the-art long-read assemblers. Second, we performed long-read sequencing of the sheep microbiome and applied metaFlye to reconstruct 63 complete or nearly complete bacterial genomes within single contigs. Finally, we show that long-read assembly of human microbiomes enables the discovery of full-length biosynthetic gene clusters that encode biomedically important natural products.", "date": "2020-11-01T00:00:00Z", "citationCount": 511, "authors": [ { "name": "Kolmogorov M." }, { "name": "Bickhart D.M." }, { "name": "Behsaz B." }, { "name": "Gurevich A." }, { "name": "Rayko M." }, { "name": "Shin S.B." }, { "name": "Kuhn K." }, { "name": "Yuan J." }, { "name": "Polevikov E." }, { "name": "Smith T.P.L." }, { "name": "Pevzner P.A." } ], "journal": "Nature Methods" } } ], "credit": [ { "name": "Mikhail Kolmogorov", "email": "fenderglass@gmail.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Support" ], "note": null }, { "name": "Yu Lin", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jeffrey Yuan", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "Pub2Tools", "additionDate": "2019-11-14T20:08:20Z", "lastUpdate": "2025-06-18T10:20:03.775603Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Genomics 2 Proteins portal", "description": "Genomics 2 Proteins (G2P) is a browser-based portal that lets you paste or upload variants and instantly map them onto PDB or AlphaFold structures. The viewer overlays UniProt domains, PTMs, disorder, conservation, and public variant tracks such as ClinVar, gnomAD, and HGMD, highlights 3-D hotspots, and can export a combined TSV or PyMOL session. Everything runs in the browser with no installation required, and a REST API is available for batch use.", "homepage": "https://g2p.broadinstitute.org", "biotoolsID": "genomics_2_proteins_portal", "biotoolsCURIE": "biotools:genomics_2_proteins_portal", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2429", "term": "Mapping" }, { "uri": "http://edamontology.org/operation_0570", "term": "Structure visualisation" }, { "uri": "http://edamontology.org/operation_0564", "term": "Sequence visualisation" }, { "uri": "http://edamontology.org/operation_0361", "term": "Sequence annotation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Bioinformatics portal" ], "topic": [ { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1038/s41592-024-02409-0", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Genomics 2 Proteins portal: a resource and discovery tool for linking genetic screening outputs to protein sequences and structures", "abstract": "Recent advances in AI-based methods have revolutionized the field of structural biology. Concomitantly, high-throughput sequencing and functional genomics have generated genetic variants at an unprecedented scale. However, efficient tools and resources are needed to link disparate data types—to ‘map’ variants onto protein structures, to better understand how the variation causes disease, and thereby design therapeutics. Here we present the Genomics 2 Proteins portal (https://g2p.broadinstitute.org/): a human proteome-wide resource that maps 20,076,998 genetic variants onto 42,413 protein sequences and 77,923 structures, with a comprehensive set of structural and functional features. Additionally, the Genomics 2 Proteins portal allows users to interactively upload protein residue-wise annotations (for example, variants and scores) as well as the protein structure beyond databases to establish the connection between genomics to proteins. The portal serves as an easy-to-use discovery tool for researchers and scientists to hypothesize the structure–function relationship between natural or synthetic variations and their molecular phenotypes.", "date": "2024-10-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Kwon S." }, { "name": "Safer J." }, { "name": "Nguyen D.T." }, { "name": "Hoksza D." }, { "name": "May P." }, { "name": "Arbesfeld J.A." }, { "name": "Rubin A.F." }, { "name": "Campbell A.J." }, { "name": "Burgin A." }, { "name": "Iqbal S." } ], "journal": "Nature Methods" } } ], "credit": [], "owner": "unethical", "additionDate": "2025-06-15T04:45:08.927267Z", "lastUpdate": "2025-06-15T04:51:27.735002Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Bracken", "description": "Bracken is a companion program to Kraken 1, KrakenUniq, or Kraken 2 While Kraken classifies reads to multiple levels in the taxonomic tree, Bracken allows estimation of abundance at a single level using those classifications (e.g. Bracken can estimate abundance of species within a sample).", "homepage": "https://ccb.jhu.edu/software/bracken/", "biotoolsID": "bracken", "biotoolsCURIE": "biotools:bracken", "version": [], "otherID": [], "relation": [ { "biotoolsID": "kraken2", "type": "uses" } ], "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": 1084, "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": "2025-06-11T12:25:29.118910Z", "editPermission": { "type": "group", "authors": [ "animalandcropgenomics", "ELIXIR-CZ", "bebatut", "vashokan" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MR-based DIPG tumour detection and segmentation (EUCAIM-SW-020_T-01-02-003)", "description": "The tool performs an automatic segmentation of the possible DIPG tumours on MR images.", "homepage": "https://www.acim.lafe.san.gva.es/acim/?page_id=675&lang=es", "biotoolsID": "mr-based_dipg_tumour_detection_and_segmentation", "biotoolsCURIE": "biotools:mr-based_dipg_tumour_detection_and_segmentation", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_2640", "term": "Oncology" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [ "EUCAIM" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.linkedin.com/company/grupo-de-investigaci%C3%B3n-biom%C3%A9dica-en-imagen/", "type": [ "Social media" ], "note": null } ], "download": [], "documentation": [ { "url": "https://link.springer.com/article/10.1007/s10278-025-01557-9", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1007/s10278-025-01557-9", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "GIBI230 - HULAFE", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "casopon", "additionDate": "2025-05-29T09:19:51.404419Z", "lastUpdate": "2025-06-05T08:53:03.701212Z", "editPermission": { "type": "group", "authors": [ "pedromiguel_martinez_HULAFE" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Denoising-Inhomogeneity Correction Tool (EUCAIM-SW-015_T-01-01-015)", "description": "A customisable image pre-processing tool that performs 5 of the most common denoising filters and ANTS N4 bias field correction filter.", "homepage": "https://www.acim.lafe.san.gva.es/acim/?page_id=675&lang=es", "biotoolsID": "denoising-inhomogeneity_correction_tool", "biotoolsCURIE": "biotools:denoising-inhomogeneity_correction_tool", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0219", "term": "Data curation and archival" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [ "EUCAIM" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.linkedin.com/company/grupo-de-investigaci%C3%B3n-biom%C3%A9dica-en-imagen/", "type": [ "Social media" ], "note": null } ], "download": [], "documentation": [ { "url": "https://drive.google.com/file/d/1W0aHAIG_bdU9Z1J3aDNsb1r39WBuX9Ot/view?usp=drive_link", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1007/s10278-021-00512-8", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "MR Denoising Increases Radiomic Biomarker Precision and Reproducibility in Oncologic Imaging", "abstract": "Several noise sources, such as the Johnson–Nyquist noise, affect MR images disturbing the visualization of structures and affecting the subsequent extraction of radiomic data. We evaluate the performance of 5 denoising filters (anisotropic diffusion filter (ADF), curvature flow filter (CFF), Gaussian filter (GF), non-local means filter (NLMF), and unbiased non-local means (UNLMF)), with 33 different settings, in T2-weighted MR images of phantoms (N = 112) and neuroblastoma patients (N = 25). Filters were discarded until the most optimal solutions were obtained according to 3 image quality metrics: peak signal-to-noise ratio (PSNR), edge-strength similarity–based image quality metric (ESSIM), and noise (standard deviation of the signal intensity of a region in the background area). The selected filters were ADFs and UNLMs. From them, 107 radiomics features preservation at 4 progressively added noise levels were studied. The ADF with a conductance of 1 and 2 iterations standardized the radiomic features, improving reproducibility and quality metrics.", "date": "2021-10-01T00:00:00Z", "citationCount": 10, "authors": [ { "name": "Fernandez Paton M." }, { "name": "Cerda Alberich L." }, { "name": "Sanguesa Nebot C." }, { "name": "Martinez de las Heras B." }, { "name": "Veiga Canuto D." }, { "name": "Canete Nieto A." }, { "name": "Marti-Bonmati L." } ], "journal": "Journal of Digital Imaging" } } ], "credit": [ { "name": "GIBI230 - HULAFE", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "casopon", "additionDate": "2025-05-29T08:55:46.088021Z", "lastUpdate": "2025-06-05T08:49:36.367527Z", "editPermission": { "type": "group", "authors": [ "pedromiguel_martinez_HULAFE" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "ML model for MR series categorisation (EUCAIM-SW-011_T-01-01-011)", "description": "AI tool that is able to perform a categorisation of MR series by using standardized DICOM tags. The categorisation includes the type of sequence (e.g. spin echo, gradient echo), the weighting (e.g. T1W, T2W, DCE, ...), the presence of fat suppression and the detection of non-relevant / junk series (e.g. localizers, calibrations, screenshots...).", "homepage": "https://www.acim.lafe.san.gva.es/acim/?page_id=675&lang=es", "biotoolsID": "ml_model_for_mr_series_categorisation", "biotoolsCURIE": "biotools:ml_model_for_mr_series_categorisation", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3345", "term": "Data identity and mapping" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": null, "collectionID": [ "EUCAIM" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.linkedin.com/company/grupo-de-investigaci%C3%B3n-biom%C3%A9dica-en-imagen/", "type": [ "Social media" ], "note": null } ], "download": [], "documentation": [ { "url": "https://journalofbigdata.springeropen.com/articles/10.1186/s40537-025-01086-w", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1186/s40537-025-01086-w", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Automatic magnetic resonance imaging series labelling for large repositories", "abstract": "Large medical image repositories present challenges related to unstructured data. A data enrichment process allows the storage of additional information for fast identification of the content and properties of medical imaging studies. The aim of this study is to develop a metadata enrichment pipeline to facilitate the secondary use of medical images in a high-throughput environment. Our aim was to develop a categorization tool for the MR series to generate standardized tags that identify relevant image characteristics such as patient orientation, sequence type, weighting type, or the presence of fat suppression. Three models that make use of machine learning (ML) and DICOM tags are proposed. The dataset for their development consists of 4666 MR series from cancer patients, labeled by expert radiologists and acquired from different manufacturers, clinical centers and anatomical regions, covering as much variability as possible with the aim of making the models generalizable to other databases. Moreover, the inference performance of the end system has been evaluated on 25,596 MR series as well as the final model outputs with an external evaluation set of 1286 MR series. The weighting model achieves very reliable results with a f1 score of 88% in the validation set. Junk and chemical shift models achieved scores of 82% and 83% respectively. These results open the door to the automatic application of image post-processing and deep learning algorithms after accurate labeling, minimizing human intervention. Furthermore, the proposed solution can infer thousands of DICOM series in less than one minute. Thanks to the fast inference times provided by this solution, it fits well in a big data ecosystem, eliminating any performance issues on ingestion in a semi-real-time environment.", "date": "2025-12-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Gomis-Maya A." }, { "name": "Cerda-Alberich L." }, { "name": "Veiga-Canuto D." }, { "name": "Claudio-Fanni S." }, { "name": "Ten-Steve A." }, { "name": "Ribas-Despuig G." }, { "name": "Mallol-Rosello P.J." }, { "name": "Vila-Frances J." }, { "name": "Marti-Bonmati L." } ], "journal": "Journal of Big Data" } } ], "credit": [ { "name": "GIBI230 - HULAFE", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "casopon", "additionDate": "2025-05-29T08:46:55.065078Z", "lastUpdate": "2025-06-05T08:47:44.651751Z", "editPermission": { "type": "group", "authors": [ "pedromiguel_martinez_HULAFE" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null } ] }
