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Applying adequate QC introduces new challenges in the genomics field where large amounts of data are produced with complex technologies. For DNA microarrays, specific algorithms for QC and pre-processing including normalization have been developed by the scientific community, especially for expression chips of the Affymetrix platform. Many of these have been implemented in the statistical scripting language R and are available from the Bioconductor repository. However, application is hampered by lack of integrative tools that can be used by users of any experience level. To fill this gap, we developed a freely available tool for QC and pre-processing of Affymetrix gene expression results, extending, integrating and harmonizing functionality of Bioconductor packages. The tool can be easily accessed through a wizard-like web portal at http://www.arrayanalysis.org or downloaded for local use in R. The portal provides extensive documentation, including user guides, interpretation help with real output illustrations and detailed technical documentation. It assists newcomers to the field in performing state-of-the-art QC and pre-processing while offering data analysts an integral open-source package. Providing the scientific community with this easily accessible tool will allow improving data quality and reuse and adoption of standards.", "date": "2013-01-01T00:00:00Z", "citationCount": 107, "authors": [ { "name": "Eijssen L.M." }, { "name": "Jaillard M." }, { "name": "Adriaens M.E." }, { "name": "Gaj S." }, { "name": "de Groot P.J." }, { "name": "Muller M." }, { "name": "Evelo C.T." } ], "journal": "Nucleic acids research" } }, { "doi": "10.1186/s12864-015-1689-8", "pmid": "26122086", "pmcid": "PMC4486126", "type": [], "version": null, "note": null, "metadata": { "title": "A user-friendly workflow for analysis of Illumina gene expression bead array data available at the arrayanalysis.org portal", "abstract": "Background: Illumina whole-genome expression bead arrays are a widely used platform for transcriptomics. Most of the tools available for the analysis of the resulting data are not easily applicable by less experienced users. 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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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": "2016-12-19T14:24:18Z", "lastUpdate": "2025-08-27T10:48:08.675794Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "datmat", "description": "‘datmat’ is a Python package aimed to easily gather data from a variety of sources and materialize it into a standardized format. 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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": "MacSyLib", "description": "a Python package library that allow to model and detect macromolecular systems, genetic pathways… by similarity search in prokaryotes datasets.", "homepage": "https://github.com/gem-pasteur/macsylib", "biotoolsID": "macsylib", "biotoolsCURIE": "biotools:macsylib", "version": [ "1.0.1" ], "otherID": [], "relation": [ { "biotoolsID": "macsyfinder", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3672", "term": "Gene functional annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2886", "term": "Protein sequence record" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3949", "term": "Profile HMM" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1245", "term": "Sequence cluster (protein)" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0085", "term": "Functional genomics" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [ "GEM Pasteur" ], "maturity": "Mature", "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/gem-pasteur/macsylib", "type": [ "Repository" ], "note": null }, { "url": "https://pypi.org/project/MacSyLib/", "type": [ "Other" ], "note": null }, { "url": "https://macsylib.readthedocs.io/en/latest/", "type": [ "Other" ], "note": null } ], "download": [ { "url": "https://github.com/gem-pasteur/macsylib", "type": "Source code", "note": null, "version": "1.0.1" }, { "url": "https://pypi.org/project/MacSyLib/", "type": "Software package", "note": null, "version": "1.0.1" } ], "documentation": [ { "url": "https://macsylib.readthedocs.io/en/latest/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.24072/pcjournal.250", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "MacSyFinder v2: Improved modelling and search engine to identify molecular systems in genomes", "abstract": "Complex cellular functions are usually encoded by a set of genes in one or a few orga-nized genetic loci in microbial genomes. 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. Finally, we have updated and improved MacSyFinder popular mod-els: TXSScan to identify protein secretion systems, TFFscan to identify type IV filaments, CONJscan to identify conjugative systems, and CasFinder to identify CRISPR associated proteins. MacSyFinder and the updated models are available at: https://github.com/gem-pasteur/macsyfinder.", "date": "2023-01-01T00:00:00Z", "citationCount": 43, "authors": [ { "name": "Neron B." }, { "name": "Denise R." }, { "name": "Coluzzi C." }, { "name": "Touchon M." }, { "name": "Rocha E.P.C." }, { "name": "Abby S.S." } ], "journal": "Peer Community Journal" } } ], "credit": [ { "name": "Institut Pasteur", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": "0495fxg12", "fundrefid": null, "typeEntity": "Institute", "typeRole": [], "note": null }, { "name": "Microbial Evolutionary Genomics Unit", "email": null, "url": "https://research.pasteur.fr/en/team/microbial-evolutionary-genomics/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [], "note": null }, { "name": "Bioinformatics and Biostatistics HUB", "email": null, "url": "https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [], "note": null }, { "name": "Eduardo P.C. Rocha", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-7704-822X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Sophie Abby", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-5231-3346", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Bertrand Néron", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0002-0220-0482", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "bneron", "additionDate": "2025-08-07T10:25:22.118390Z", "lastUpdate": "2025-08-11T12:14:42.322020Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "hictkpy", "description": "Python bindings for hictk: read and write .cool and .hic files directly from Python", "homepage": "https://github.com/paulsengroup/hictkpy", "biotoolsID": "hictkpy", "biotoolsCURIE": "biotools:hictkpy", "version": [ "0.0.1", "0.0.2", "0.0.3", "0.0.4", "0.0.5", "1.0.0", "1.1.0", "1.2.0", "1.3.0" ], "otherID": [], "relation": [ { "biotoolsID": "hictk", "type": "uses" } ], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/paulsengroup/hictkpy", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/paulsengroup/hictkpy/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/paulsengroup/hictkpy/discussions", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://github.com/paulsengroup/hictkpy/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://pypi.org/project/hictkpy/", "type": "Binaries", "note": null, "version": null }, { "url": "https://anaconda.org/bioconda/hictkpy", "type": "Binaries", "note": null, "version": null } ], "documentation": [ { "url": "https://hictkpy.readthedocs.io", "type": [ "General" ], "note": null }, { "url": "https://hictkpy.readthedocs.io/en/stable/installation.html", "type": [ "Installation instructions" ], "note": null }, { "url": "https://hictkpy.readthedocs.io/en/stable/quickstart.html", "type": [ "Quick start guide" ], "note": null }, { "url": "https://hictkpy.readthedocs.io/en/stable/api/index.html", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btae408", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "hictk: blazing fast toolkit to work with. hic and. cool files", "abstract": "Motivation: Hi-C is gaining prominence as a method for mapping genome organization. With declining sequencing costs and a growing demand for higher-resolution data, efficient tools for processing Hi-C datasets at different resolutions are crucial. Over the past decade, the. hic and Cooler file formats have become the de-facto standard to store interaction matrices produced by Hi-C experiments in binary format. Interoperability issues make it unnecessarily difficult to convert between the two formats and to develop applications that can process each format natively. Results: We developed hictk, a toolkit that can transparently operate on. hic and. cool files with excellent performance. The toolkit is written in C++ and consists of a C++ library with Python and R bindings as well as CLI tools to perform common operations directly from the shell, including converting between. hic and. mcool formats. We benchmark the performance of hictk and compare it with other popular tools and libraries. We conclude that hictk significantly outperforms existing tools while providing the flexibility of natively working with both file formats without code duplication.", "date": "2024-07-01T00:00:00Z", "citationCount": 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": "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": "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. 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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, 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{ "uri": "http://edamontology.org/operation_2437", "term": "Gene regulatory network prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2603", "term": "Expression data" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] }, { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_1288", "term": "Genome map" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_3002", "term": "Annotation track" }, "format": [ { "uri": "http://edamontology.org/format_2306", "term": "GTF" }, { "uri": "http://edamontology.org/format_2305", "term": "GFF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2887", "term": "Nucleic acid sequence record" }, "format": [ { "uri": 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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" } ] }
