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Complete source code is on GitHub, but most platforms have an installer anyway; see the manual, chapter 2, for installation instructions.", "version": null }, { "url": "https://github.com/MesserLab/SLiM/releases/latest", "type": "Downloads page", "note": "The GitHub page for the current release version, to obtain full source code.", "version": null } ], "documentation": [ { "url": "http://benhaller.com/slim/SLiM_Manual.pdf", "type": [ "User manual" ], "note": "The manual for SLiM itself" }, { "url": "http://benhaller.com/slim/Eidos_Manual.pdf", "type": [ "User manual" ], "note": "The manual for Eidos, the scripting language used by SLiM" }, { "url": "http://benhaller.com/slim/SLiMEidosRefSheets.zip", "type": [ "Quick start guide" ], "note": "Quick reference sheets for SLiM and Eidos" } ], "publication": [ { "doi": "10.1093/molbev/msy228", "pmid": "30517680", "pmcid": "PMC6389312", "type": [ "Primary" ], "version": "3.0", "note": "B.C. Haller, P.W. Messer. (2019). 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Ralph. (2019). Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes. Molecular Ecology Resources 19(2), 552–566.", "metadata": { "title": "Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes", "abstract": "", "date": "2019-03-01T00:00:00Z", "citationCount": 123, "authors": [], "journal": "Molecular Ecology Resources" } }, { "doi": "10.1101/2025.08.07.669155", "pmid": "40832315", "pmcid": "PMC12363870", "type": [ "Primary" ], "version": "5.0", "note": "BC Haller, PL Ralph, PW Messer. (2025). SLiM 5: Eco-evolutionary simulations across multiple chromosomes and full genomes. bioRxiv, 2025.08. 07.669155", "metadata": null }, { "doi": "10.1086/723601", "pmid": "37130229", "pmcid": "PMC10793872", "type": [ "Primary" ], "version": "4.0", "note": "B.C. Haller, P.W. Messer. (2023). SLiM 4: Multispecies eco-evolutionary modeling. 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Macromolecular System Finder (MacSyFinder) is a program that uses these properties to model and then annotate cellular functions in microbial genomes. This is done by integrating the identification of each individual gene at the level of the molecular system. We hereby present a major release of MacSyFinder (version 2) coded in Python 3. The code was improved and rationalized to facilitate future maintainability. Several new features were added to allow more flexible modelling of the systems. We introduce a more intuitive and comprehensive search engine to identify all the best candidate systems and sub-optimal ones that respect the models’ constraints. We also introduce the novel macsydata companion tool that enables the easy installation and broad distribution of the models developed for MacSyFinder (macsy-models) from GitHub repositories. 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With declining sequencing costs and a growing demand for higher-resolution data, efficient tools for processing Hi-C datasets at different resolutions are crucial. Over the past decade, the. hic and Cooler file formats have become the de-facto standard to store interaction matrices produced by Hi-C experiments in binary format. Interoperability issues make it unnecessarily difficult to convert between the two formats and to develop applications that can process each format natively. Results: We developed hictk, a toolkit that can transparently operate on. hic and. cool files with excellent performance. The toolkit is written in C++ and consists of a C++ library with Python and R bindings as well as CLI tools to perform common operations directly from the shell, including converting between. hic and. mcool formats. We benchmark the performance of hictk and compare it with other popular tools and libraries. We conclude that hictk significantly outperforms existing tools while providing the flexibility of natively working with both file formats without code duplication.", "date": "2024-07-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Rossini R." }, { "name": "Paulsen J." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "robomics", "additionDate": "2024-04-18T08:31:46.459964Z", "lastUpdate": "2025-08-04T21:44:58.121944Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "hictk", "description": "Blazing fast toolkit to work with .hic and .cool files", "homepage": "https://github.com/paulsengroup/hictk", "biotoolsID": "hictk", "biotoolsCURIE": "biotools:hictk", "version": [ "1.0.0", "2.0.0", "2.0.1", "2.0.2", "2.1.0", "2.1.1", "2.1.2", "2.1.3", "2.1.4" ], "otherID": [], "relation": [ { "biotoolsID": "hictkpy", "type": "usedBy" }, { "biotoolsID": "hictkr", "type": "usedBy" } ], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/paulsengroup/hictk", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/paulsengroup/hictk/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/paulsengroup/hictk/discussions", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://github.com/paulsengroup/hictk/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://anaconda.org/bioconda/hictk", "type": "Binaries", "note": null, "version": null }, { "url": "https://github.com/paulsengroup/hictk/pkgs/container/hictk", "type": "Container file", "note": null, "version": null } ], "documentation": [ { "url": "https://hictk.readthedocs.io", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btae408", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "hictk: blazing fast toolkit to work with. hic and. cool files", "abstract": "Motivation: Hi-C is gaining prominence as a method for mapping genome organization. With declining sequencing costs and a growing demand for higher-resolution data, efficient tools for processing Hi-C datasets at different resolutions are crucial. Over the past decade, the. hic and Cooler file formats have become the de-facto standard to store interaction matrices produced by Hi-C experiments in binary format. Interoperability issues make it unnecessarily difficult to convert between the two formats and to develop applications that can process each format natively. Results: We developed hictk, a toolkit that can transparently operate on. hic and. cool files with excellent performance. The toolkit is written in C++ and consists of a C++ library with Python and R bindings as well as CLI tools to perform common operations directly from the shell, including converting between. hic and. mcool formats. We benchmark the performance of hictk and compare it with other popular tools and libraries. We conclude that hictk significantly outperforms existing tools while providing the flexibility of natively working with both file formats without code duplication.", "date": "2024-07-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Rossini R." }, { "name": "Paulsen J." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "robomics", "additionDate": "2024-02-02T14:42:46.030561Z", "lastUpdate": "2025-08-04T21:43:36.678557Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "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. 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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": "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. 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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": "OakMine", "description": "Quercus robur annotation database", "homepage": "https://urgi.versailles.inra.fr/OakMine_PM1N", "biotoolsID": "OakMine", "biotoolsCURIE": "biotools:OakMine", "version": [ "2.3" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2436", "term": "Gene-set enrichment analysis" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1255", "term": "Sequence features" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3753", "term": "Over-representation data" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3786", "term": "Query script" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1255", "term": "Sequence features" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web service", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3071", "term": "Data management" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "R", "Ruby", "Java", "Python", "JavaScript", "Perl" ], "license": "LGPL-2.1", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://registry.intermine.org", "type": [ "Software catalogue" ], "note": null }, { "url": "http://intermine.org", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [ { "url": "http://intermine.readthedocs.org/en/latest/web-services/", "type": [ "API documentation" ], "note": null }, { "url": "https://flymine.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/bts577", "pmid": "23023984", "pmcid": "PMC3516146", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "InterMine: A flexible data warehouse system for the integration and analysis of heterogeneous biological data", "abstract": "InterMine is an open-source data warehouse system that facilitates the building of databases with complex data integration requirements and a need for a fast customizable query facility. Using InterMine, large biological databases can be created from a range of heterogeneous data sources, and the extensible data model allows for easy integration of new data types. The analysis tools include a flexible query builder, genomic region search and a library of 'widgets' performing various statistical analyses. The results can be exported in many commonly used formats. InterMine is a fully extensible framework where developers can add new tools and functionality. Additionally, there is a comprehensive set of web services, for which client libraries are provided in five commonly used programming languages. © The Author 2012. Published by Oxford University Press. All rights reserved.", "date": "2012-12-01T00:00:00Z", "citationCount": 202, "authors": [ { "name": "Smith R.N." }, { "name": "Aleksic J." }, { "name": "Butano D." }, { "name": "Carr A." }, { "name": "Contrino S." }, { "name": "Hu F." }, { "name": "Lyne M." }, { "name": "Lyne R." }, { "name": "Kalderimis A." }, { "name": "Rutherford K." }, { "name": "Stepan R." }, { "name": "Sullivan J." }, { "name": "Wakeling M." }, { "name": "Watkins X." }, { "name": "Micklem G." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "InterMine", "additionDate": "2019-11-27T10:47:08Z", "lastUpdate": "2025-07-29T13:42:35.424110Z", "editPermission": { "type": "group", "authors": [ "cmichotey" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "GrapeMine", "description": "An integrated database for grapevine data", "homepage": "http://urgi.versailles.inra.fr/GrapeMine", "biotoolsID": "GrapeMine", "biotoolsCURIE": "biotools:GrapeMine", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2436", "term": "Gene-set enrichment analysis" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1255", "term": "Sequence features" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3753", "term": "Over-representation data" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3786", "term": "Query script" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1255", "term": "Sequence features" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web service", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3071", "term": "Data management" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "R", "Ruby", "Java", "Python", "JavaScript", "Perl" ], "license": "LGPL-2.1", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://registry.intermine.org", "type": [ "Software catalogue" ], "note": null }, { "url": "http://intermine.org", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [ { "url": "http://intermine.readthedocs.org/en/latest/web-services/", "type": [ "API documentation" ], "note": null }, { "url": "https://flymine.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/bts577", "pmid": "23023984", "pmcid": "PMC3516146", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "InterMine: A flexible data warehouse system for the integration and analysis of heterogeneous biological data", "abstract": "InterMine is an open-source data warehouse system that facilitates the building of databases with complex data integration requirements and a need for a fast customizable query facility. Using InterMine, large biological databases can be created from a range of heterogeneous data sources, and the extensible data model allows for easy integration of new data types. The analysis tools include a flexible query builder, genomic region search and a library of 'widgets' performing various statistical analyses. The results can be exported in many commonly used formats. InterMine is a fully extensible framework where developers can add new tools and functionality. Additionally, there is a comprehensive set of web services, for which client libraries are provided in five commonly used programming languages. © The Author 2012. Published by Oxford University Press. All rights reserved.", "date": "2012-12-01T00:00:00Z", "citationCount": 202, "authors": [ { "name": "Smith R.N." }, { "name": "Aleksic J." }, { "name": "Butano D." }, { "name": "Carr A." }, { "name": "Contrino S." }, { "name": "Hu F." }, { "name": "Lyne M." }, { "name": "Lyne R." }, { "name": "Kalderimis A." }, { "name": "Rutherford K." }, { "name": "Stepan R." }, { "name": "Sullivan J." }, { "name": "Wakeling M." }, { "name": "Watkins X." }, { "name": "Micklem G." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "InterMine", "additionDate": "2019-11-27T10:46:35Z", "lastUpdate": "2025-07-29T13:42:33.883794Z", "editPermission": { "type": "group", "authors": [ "cmichotey" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "WheatMine", "description": "Wheat IWGSC RefSeq v1.0", "homepage": "https://urgi.versailles.inra.fr/WheatMine", "biotoolsID": "WheatMine", "biotoolsCURIE": "biotools:WheatMine", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2436", "term": "Gene-set enrichment analysis" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1255", "term": "Sequence features" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3753", "term": "Over-representation data" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3786", "term": "Query script" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1255", "term": "Sequence features" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Web service", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3071", "term": "Data management" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "R", "Ruby", "Java", "Python", "JavaScript", "Perl" ], "license": "LGPL-2.1", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://registry.intermine.org", "type": [ "Software catalogue" ], "note": null }, { "url": "http://intermine.org", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [ { "url": "http://intermine.readthedocs.org/en/latest/web-services/", "type": [ "API documentation" ], "note": null }, { "url": "https://flymine.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/bts577", "pmid": "23023984", "pmcid": "PMC3516146", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "InterMine: A flexible data warehouse system for the integration and analysis of heterogeneous biological data", "abstract": "InterMine is an open-source data warehouse system that facilitates the building of databases with complex data integration requirements and a need for a fast customizable query facility. 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All rights reserved.", "date": "2012-12-01T00:00:00Z", "citationCount": 202, "authors": [ { "name": "Smith R.N." }, { "name": "Aleksic J." }, { "name": "Butano D." }, { "name": "Carr A." }, { "name": "Contrino S." }, { "name": "Hu F." }, { "name": "Lyne M." }, { "name": "Lyne R." }, { "name": "Kalderimis A." }, { "name": "Rutherford K." }, { "name": "Stepan R." }, { "name": "Sullivan J." }, { "name": "Wakeling M." }, { "name": "Watkins X." }, { "name": "Micklem G." } ], "journal": "Bioinformatics" } } ], "credit": [], "owner": "InterMine", "additionDate": "2019-11-27T10:47:40Z", "lastUpdate": "2025-07-29T13:42:33.209390Z", "editPermission": { "type": "group", "authors": [ "cmichotey" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "XNATpy", "description": "Python package to interact with the XNAT REST API in a python data-science way", "homepage": "https://gitlab.com/radiology/infrastructure/xnatpy", "biotoolsID": "xnatpy", "biotoolsCURIE": "biotools:xnatpy", "version": [], "otherID": [], "relation": [ { "biotoolsID": "xnat-pic", "type": "usedBy" }, { "biotoolsID": "xnat", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Data deposition" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3071", "term": "Data management" }, { "uri": "http://edamontology.org/topic_4012", "term": "FAIR data" }, { "uri": "http://edamontology.org/topic_3384", "term": "Medical imaging" } ], "operatingSystem": [ "Windows", "Linux", "Mac" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [ "EUCAIM" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://gitlab.com/radiology/infrastructure/xnatpy/", "type": [ "Repository" ], "note": null }, { "url": "https://gitlab.com/radiology/infrastructure/xnatpy/-/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://pypi.org/project/xnat/", "type": [ "Software catalogue" ], "note": null }, { "url": "https://anaconda.org/conda-forge/xnat", "type": [ "Software catalogue" ], "note": null } ], "download": [ { "url": "https://pypi.org/project/xnat/", "type": "Software package", "note": null, "version": null }, { "url": "https://anaconda.org/conda-forge/xnat", "type": "Software package", "note": null, "version": null } ], "documentation": [ { "url": "https://xnat.readthedocs.io/en/latest/", "type": [ "General" ], "note": null } ], "publication": [], "credit": [ { "name": "Hakim Achterberg", "email": "h.achterberg@erasmusmc.nl", "url": "https://bigr.nl/member/hakim/", "orcidid": "https://orcid.org/0000-0003-3772-4582", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer" ], "note": null }, { "name": "Erasmus MC", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "hachterberg", "additionDate": "2025-07-23T10:24:09.622930Z", "lastUpdate": "2025-07-24T08:55:06.000976Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "XNAT", "description": "XNAT is an open source imaging informatics platform developed by the Neuroinformatics Research Group at Washington University. 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": "DUNE", "description": "A versatile neuroimaging encoder for extracting deep features from multisequence brain MRIs", "homepage": "https://github.com/gevaertlab/DUNE", "biotoolsID": "GevaertLab_DUNE", "biotoolsCURIE": "biotools:GevaertLab_DUNE", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3937", "term": "Feature extraction" } ], "input": [], "output": [], "note": "Extracts features from", "cmd": "python -m src.main process /path/to/dicom/folder /path/to/output" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3384", "term": "Medical imaging" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/gevaertlab/DUNE", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/gevaertlab/DUNE", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/gevaertlab/DUNE/blob/main/README.md", "type": [ "Quick start guide" ], "note": null } ], "publication": [ { "doi": "10.1101/2025.02.24.25322787", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Thomas Barba", "email": "thomas.barba@inserm.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "tbarba", "additionDate": "2025-07-15T16:04:03.513732Z", "lastUpdate": "2025-07-15T16:04:03.516083Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "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": "ColoPola dataset for colorectal cancer detection", "description": "The dataset consists of 572 slices (specimens) with 20,592 images. There are 284 cancer samples and 288 normal samples. The lists of samples for training (train+val) set and testing set are provided in the Zenodo repository. Source code in Github is to train and validate five deep learning models using ColoPola dataset.", "homepage": "https://github.com/haile493/Colorectal-cancer-detection-using-ColoPola-dataset", "biotoolsID": "colopola_dataset_for_colorectal_cancer_detection", "biotoolsCURIE": "biotools:colopola_dataset_for_colorectal_cancer_detection", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_3316", "term": "Computer science" } ], "operatingSystem": [ "Windows" ], "language": [ "Python" ], "license": "CC0-1.0", "collectionID": [ "Dataset" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/haile493/Colorectal-cancer-detection-using-ColoPola-dataset", "type": [ "Repository" ], "note": "Source code" }, { "url": "https://github.com/haile493/Colorectal-cancer-detection-using-ColoPola-dataset/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://github.com/haile493/Colorectal-cancer-detection-using-ColoPola-dataset", "type": "Source code", "note": "Python language", "version": "1.0" }, { "url": "https://zenodo.org/records/10554304", "type": "Test data", "note": "Dataset for running source code", "version": "1.2" } ], "documentation": [], "publication": [], "credit": [], "owner": "haile", "additionDate": "2025-07-10T03:21:50.923918Z", "lastUpdate": "2025-07-10T03:33:52.616431Z", "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": "basico", "description": "BASICO, a simplified Python interface to COPASI. It provides a set of functions\n that allow to create, edit, simulate and analyze models in an automated way", "homepage": "https://basico.readthedocs.io/en/latest/", "biotoolsID": "basico", "biotoolsCURIE": "biotools:basico", "version": [], "otherID": [], "relation": [ { "biotoolsID": "copasi", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3660", "term": "Metabolic network modelling" }, { "uri": "http://edamontology.org/operation_3928", "term": "Pathway analysis" }, { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3241", "term": "Kinetic model" }, "format": [ { "uri": "http://edamontology.org/format_3239", "term": "CopasiML" }, { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "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_3241", "term": "Kinetic model" }, "format": [ { "uri": "http://edamontology.org/format_3239", "term": "CopasiML" }, { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_3685", "term": "SED-ML" }, { "uri": "http://edamontology.org/format_3686", "term": "COMBINE OMEX" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library", "Script" ], "topic": [ { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "Artistic-2.0", "collectionID": [ "de.NBI" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://pypi.org/project/copasi-basico/", "type": "Source code", "note": null, "version": null } ], "documentation": [], "publication": [ { "doi": "10.21105/joss.05553", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": null } ], "credit": [ { "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", "Developer" ], "note": null } ], "owner": "frankbergmann", "additionDate": "2025-02-26T14:07:27.855714Z", "lastUpdate": "2025-07-07T11:16:29.397538Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "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. 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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. 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Here, we describe novel tools for summarizing experiments, filtering datasets, visualizing phased alignments results, and updates to the NanoPack software suite. Availability and implementation: The cramino, chopper, kyber, and phasius tools are written in Rust and available as executable binaries without requiring installation or managing dependencies. Binaries build on musl are available for broad compatibility. NanoPlot and NanoComp are written in Python3. Links to the separate tools and their documentation can be found at https://github.com/wdecoster/nanopack. All tools are compatible with Linux, Mac OS, and the MS Windows Subsystem for Linux and are released under the MIT license. 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