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null, "note": null, "metadata": { "title": "Gradations in protein dynamics captured by experimental NMR are not well represented by AlphaFold2 models and other computational metrics", "abstract": "", "date": "2025-01-15T00:00:00Z", "citationCount": 3, "authors": [], "journal": "Journal of Molecular Biology" } } ], "credit": [ { "name": "Wim Vranken", "email": "wim.vranken@vub.be", "url": "https://bio2byte.be/people/31", "orcidid": "https://orcid.org/0000-0001-7470-4324", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "W.V., D.R. and G.O. conceptualised the study. W.V., D.R., G.O. and D.B. provided supervision. W.V. provided the NMR data and directed the project." }, { "name": "José Gavalda-Garcia", "email": null, "url": "https://bio2byte.be/people/38", "orcidid": "https://orcid.org/0000-0001-6431-3442", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "J.G.-G. and D.B. developed, implemented and validated the method." }, { "name": "David Bickel", "email": null, "url": "https://bio2byte.be/people/47", "orcidid": "https://orcid.org/0000-0003-0332-8338", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "W.V., D.R., G.O. and D.B. provided supervision. 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Such an environment should be able to fulfill the different needs and requirements arising from both the growing use of 2-DE techniques and the increasing amount of distributed experimental data.", "date": "2003-08-01T00:00:00Z", "citationCount": 27, "authors": [ { "name": "Mostaguir K." }, { "name": "Hoogland C." }, { "name": "Binz P.-A." }, { "name": "Appel R.D." } ], "journal": "Proteomics" } } ], "credit": [ { "name": "ExPASy helpdesk", "email": null, "url": "https://www.expasy.org/support", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "admin", "additionDate": "2017-12-06T18:14:40Z", "lastUpdate": "2025-08-28T13:43:51.088758Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools" ] }, "validated": 1, "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. The web portal indexes and makes findable any kind of data from wheat related species. \nThe WheatIS search is an implementation of DataDiscovery.", "homepage": "https://urgi.versailles.inrae.fr/wheatis/", "biotoolsID": "WheatIS", "biotoolsCURIE": "biotools:WheatIS", "version": [], "otherID": [], "relation": [ { "biotoolsID": "gnpis", "type": "uses" }, { "biotoolsID": "DataDiscovery", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_3625", "term": "Relation extraction" }, { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" }, { "uri": "http://edamontology.org/operation_3908", "term": "Information retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0968", "term": "Keyword" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2093", "term": "Data reference" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web API", "Web application", "Web service", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_0610", "term": "Ecology" }, { "uri": "http://edamontology.org/topic_3071", "term": "Biological databases" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3810", "term": "Agricultural science" } ], "operatingSystem": [], "language": [], "license": "BSD-3-Clause", "collectionID": [ "elixir-fr-sdp-2019", "URGI" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools", "Data", "Interoperability" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [ { "url": "http://www.wheatis.org/", "type": [ "Other" ], "note": "WheatIS website" } ], "download": [], "documentation": [ { "url": "https://urgi.versailles.inra.fr/wheatis/about", "type": [ "General" ], "note": null }, { "url": "https://urgi.versailles.inra.fr/wheatis/join", "type": [ "Contributions policy" ], "note": null }, { "url": "https://urgi.versailles.inra.fr/wheatis/legal", "type": [ "Terms of use" ], "note": null }, { "url": "https://urgi.versailles.inra.fr/wheatis/help", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1186/s13059-018-1491-4", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": "Alaux M, Rogers J, Letellier T, Flores R, Alfama F, Pommier C, Mohellibi N, Durand S, Kimmel E, Michotey C, Guerche C, Loaec M, Lainé M, Steinbach D, Choulet F, Rimbert H, Leroy P, Guilhot N, Salse J, Feuillet C, International Wheat Genome Sequencing Consortium, Paux E, Eversole K, Adam-Blondon A-F, Quesneville H (2018) Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data. Genome Biology, 19:111", "metadata": { "title": "Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data", "abstract": "© 2018 The Author(s).The Wheat@URGI portal has been developed to provide the international community of researchers and breeders with access to the bread wheat reference genome sequence produced by the International Wheat Genome Sequencing Consortium. Genome browsers, BLAST, and InterMine tools have been established for in-depth exploration of the genome sequence together with additional linked datasets including physical maps, sequence variations, gene expression, and genetic and phenomic data from other international collaborative projects already stored in the GnpIS information system. The portal provides enhanced search and browser features that will facilitate the deployment of the latest genomics resources in wheat improvement.", "date": "2018-08-17T00:00:00Z", "citationCount": 88, "authors": [ { "name": "Alaux M." }, { "name": "Rogers J." }, { "name": "Letellier T." }, { "name": "Flores R." }, { "name": "Alfama F." }, { "name": "Pommier C." }, { "name": "Mohellibi N." }, { "name": "Durand S." }, { "name": "Kimmel E." }, { "name": "Michotey C." }, { "name": "Guerche C." }, { "name": "Loaec M." }, { "name": "Laine M." }, { "name": "Steinbach D." }, { "name": "Choulet F." }, { "name": "Rimbert H." }, { "name": "Leroy P." }, { "name": "Guilhot N." }, { "name": "Salse J." }, { "name": "Feuillet C." }, { "name": "Paux E." }, { "name": "Eversole K." }, { "name": "Adam-Blondon A.-F." }, { "name": "Quesneville H." } ], "journal": "Genome Biology" } } ], "credit": [ { "name": "Support service", "email": "urgi-support@inrae.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact", "Support" ], "note": null } ], "owner": "jison", "additionDate": "2019-11-05T10:40:37Z", "lastUpdate": "2025-07-29T13:42:41.391722Z", "editPermission": { "type": "group", "authors": [ "nfrancillon", "raphael.flores", "cmichotey" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DataDiscovery", "description": "DataDiscovery aims at providing researchers a simple and fast access to relevant biological data using specific keywords and easy to use filters.\n\nThis tool is expected to be easily customizable for specific filters, environments, or data schemas. Its current implementations supported by URGI are: WheatIS, Plant, RARe.", "homepage": "https://urgi.versailles.inrae.fr/data-discovery/", "biotoolsID": "DataDiscovery", "biotoolsCURIE": "biotools:DataDiscovery", "version": [], "otherID": [], "relation": [ { "biotoolsID": "wheatis", "type": "usedBy" }, { "biotoolsID": "RARe", "type": "usedBy" }, { "biotoolsID": "Plant_DataDiscovery", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_3625", "term": "Relation extraction" }, { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" }, { "uri": "http://edamontology.org/operation_3908", "term": "Information retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0968", "term": "Keyword" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2093", "term": "Data reference" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web API", "Web application", "Web service", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_0610", "term": "Ecology" }, { "uri": "http://edamontology.org/topic_3071", "term": "Biological databases" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3810", "term": "Agricultural science" } ], "operatingSystem": [ "Linux" ], "language": [ "JavaScript", "Java", "Bash" ], "license": "BSD-3-Clause", "collectionID": [ "elixir-fr-sdp-2019", "URGI" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data", "Tools", "Interoperability" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [ { "url": "https://forgemia.inra.fr/urgi-is/data-discovery", "type": [ "Repository" ], "note": "GitLab code repository for DataDiscovery" }, { "url": "https://github.com/gnpis/DataDiscovery/", "type": [ "Mirror" ], "note": "Code repository mirror link for DataDiscovery" } ], "download": [], "documentation": [ { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/LEGAL-MENTIONS.md", "type": [ "Terms of use" ], "note": "General terms of use" }, { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/README.md#contribute", "type": [ "Contributions policy" ], "note": "How to contribute" }, { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/HELP.md", "type": [ "User manual" ], "note": "How to use" }, { "url": "https://forgemia.inra.fr/urgi-is/data-discovery/blob/master/README.md#setup", "type": [ "Installation instructions" ], "note": "How to install" } ], "publication": [ { "doi": "10.3835/plantgenome2015.06.0038", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": "1-\tSpannagl, M., Alaux, M., Lange, M., Bolser, D. M., Bader, K. C., Letellier, T., Kimmel, E., Flores, R.-G., Pommier, C., Kerhornou, A., Walts, B., Nussbaumer, T., Grabmuller, C., Chen, J., Colmsee, C., Beier, S., Mascher, M., Schmutzer, T., Arend, D., Thanki, A., Ramirez-Gonzalez, R., Ayling, M., Ayling, S., Caccamo, M., Mayer, K. F. X., Scholz, U., Steinbach, D., Quesneville, H., Kersey, P. (2016). TransPLANT resources for triticeae genomic data. Plant Genome, 9 (1), 13 p.", "metadata": { "title": "TransPLANT resources for triticeae genomic data", "abstract": "The genome sequences of many important Triticeae species, including bread wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), remained uncharacterized for a long time because their high repeat content, large sizes, and polyploidy. As a result of improvements in sequencing technologies and novel analyses strategies, several of these have recently been deciphered. These efforts have generated new insights into Triticeae biology and genome organization and have important implications for downstream usage by breeders, experimental biologists, and comparative genomicists. transPLANT (http://www.transplantdb.eu) is an EU-funded project aimed at constructing hardware, software, and data infrastructure for genome-scale research in the life sciences. Since the Triticeae data are intrinsically complex, heterogenous, and distributed, the transPLANT consortium has undertaken efforts to develop common data formats and tools that enable the exchange and integration of data from distributed resources. Here we present an overview of the individual Triticeae genome resources hosted by transPLANT partners, introduce the objectives of transPLANT, and outline common developments and interfaces supporting integrated data access.", "date": "2016-03-01T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Spannagl M." }, { "name": "Alaux M." }, { "name": "Lange M." }, { "name": "Bolser D.M." }, { "name": "Bader K.C." }, { "name": "Letellier T." }, { "name": "Kimmel E." }, { "name": "Flores R." }, { "name": "Pommier C." }, { "name": "Kerhornou A." }, { "name": "Walts B." }, { "name": "Nussbaumer T." }, { "name": "Grabmuller C." }, { "name": "Chen J." }, { "name": "Colmsee C." }, { "name": "Beier S." }, { "name": "Mascher M." }, { "name": "Schmutzer T." }, { "name": "Arend D." }, { "name": "Thanki A." }, { "name": "Ramirez-Gonzalez R." }, { "name": "Ayling M." }, { "name": "Ayling S." }, { "name": "Caccamo M." }, { "name": "Mayer K.F.X." }, { "name": "Scholz U." }, { "name": "Steinbach D." }, { "name": "Quesneville H." }, { "name": "Kersey P.J." } ], "journal": "Plant Genome" } }, { "doi": "10.1038/hortres.2016.56", "pmid": null, "pmcid": null, "type": [], "version": null, "note": "2-\tAdam-Blondon, A.-F., Alaux, M., Pommier, C., Cantu, D., Cheng, Z.-M., Cramer, G. R., Davies, C., Delrot, S., Deluc, L., di Gaspero, G., Grimplet, J., Fennell, A., Londo, J. P., Kersey, P., Mattivi, F., Naithani, S., Neveu, P., Nikolski, M., Pezzotti, M., Reisch, B. I., Topfer, R., Vivier, M., Ware, D., Quesneville, H. (2016). Towards an open grapevine information system. Horticulture Research, 3, 8 p. , DOI : 10.1038/hortres.2016.56", "metadata": { "title": "Towards an open grapevine information system", "abstract": "Viticulture, like other fields of agriculture, is currently facing important challenges that will be addressed only through sustained, dedicated and coordinated research. Although the methods used in biology have evolved tremendously in recent years and now involve the routine production of large data sets of varied nature, in many domains of study, including grapevine research, there is a need to improve the findability, accessibility, interoperability and reusability (FAIR-ness) of these data. Considering the heterogeneous nature of the data produced, the transnational nature of the scientific community and the experience gained elsewhere, we have formed an open working group, in the framework of the International Grapevine Genome Program (www.vitaceae.org), to construct a coordinated federation of information systems holding grapevine data distributed around the world, providing an integrated set of interfaces supporting advanced data modeling, rich semantic integration and the next generation of data mining tools. To achieve this goal, it will be critical to develop, implement and adopt appropriate standards for data annotation and formatting. The development of this system, the GrapeIS, linking genotypes to phenotypes, and scientific research to agronomical and oeneological data, should provide new insights into grape biology, and allow the development of new varieties to meet the challenges of biotic and abiotic stress, environmental change, and consumer demand.", "date": "2016-11-23T00:00:00Z", "citationCount": 37, "authors": [ { "name": "Adam-Blondon A.-F." }, { "name": "Alaux M." }, { "name": "Pommier C." }, { "name": "Cantu D." }, { "name": "Cheng Z.-M." }, { "name": "Cramer G." }, { "name": "Davies C." }, { "name": "Delrot S." }, { "name": "Deluc L." }, { "name": "Di Gaspero G." }, { "name": "Grimplet J." }, { "name": "Fennell A." }, { "name": "Londo J." }, { "name": "Kersey P." }, { "name": "Mattivi F." }, { "name": "Naithani S." }, { "name": "Neveu P." }, { "name": "Nikolski M." }, { "name": "Pezzotti M." }, { "name": "Reisch B." }, { "name": "Topfer R." }, { "name": "Vivier M." }, { "name": "Ware D." }, { "name": "Quesneville H." } ], "journal": "Horticulture Research" } }, { "doi": "10.1186/s13059-018-1491-4", "pmid": null, "pmcid": null, "type": [], "version": null, "note": "3-\tAlaux M, Rogers J, Letellier T, Flores R, Alfama F, Pommier C, Mohellibi N, Durand S, Kimmel E, Michotey C, Guerche C, Loaec M, Lainé M, Steinbach D, Choulet F, Rimbert H, Leroy P, Guilhot N, Salse J, Feuillet C, International Wheat Genome Sequencing Consortium, Paux E, Eversole K, Adam-Blondon A-F, Quesneville H (2018) Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data. Genome Biology, 19:111.", "metadata": { "title": "Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data", "abstract": "The Wheat@URGI portal has been developed to provide the international community of researchers and breeders with access to the bread wheat reference genome sequence produced by the International Wheat Genome Sequencing Consortium. Genome browsers, BLAST, and InterMine tools have been established for in-depth exploration of the genome sequence together with additional linked datasets including physical maps, sequence variations, gene expression, and genetic and phenomic data from other international collaborative projects already stored in the GnpIS information system. The portal provides enhanced search and browser features that will facilitate the deployment of the latest genomics resources in wheat improvement.", "date": "2018-08-17T00:00:00Z", "citationCount": 181, "authors": [ { "name": "Alaux M." }, { "name": "Rogers J." }, { "name": "Letellier T." }, { "name": "Flores R." }, { "name": "Alfama F." }, { "name": "Pommier C." }, { "name": "Mohellibi N." }, { "name": "Durand S." }, { "name": "Kimmel E." }, { "name": "Michotey C." }, { "name": "Guerche C." }, { "name": "Loaec M." }, { "name": "Laine M." }, { "name": "Steinbach D." }, { "name": "Choulet F." }, { "name": "Rimbert H." }, { "name": "Leroy P." }, { "name": "Guilhot N." }, { "name": "Salse J." }, { "name": "Feuillet C." }, { "name": "Paux E." }, { "name": "Eversole K." }, { "name": "Adam-Blondon A.-F." }, { "name": "Quesneville H." } ], "journal": "Genome Biology" } } ], "credit": [ { "name": "urgi-support", "email": "urgi-support@inrae.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact", "Support" ], "note": null } ], "owner": "nfrancillon", "additionDate": "2020-01-21T16:40:38Z", "lastUpdate": "2025-07-29T13:42:39.375595Z", "editPermission": { "type": "group", "authors": [ "urgi-contact", "cpommier", "cmichotey", "erlefloch", "raphael.flores" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Genetic and Genomic Information System (GnpIS)", "description": "A multispecies integrative information system dedicated to plant and fungi pests.. It allows researchers to access genetic, phenotypic and genomic data. It is used by both large international projects and the French National Research Institute for Agriculture, Food and Environment", "homepage": "https://urgi.versailles.inrae.fr/gnpis", "biotoolsID": "gnpis", "biotoolsCURIE": "biotools:gnpis", "version": [ "18.2" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3208", "term": "Genome visualisation" }, { "uri": "http://edamontology.org/operation_2409", "term": "Data handling" }, { "uri": "http://edamontology.org/operation_0227", "term": "Indexing" }, { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" }, { "uri": "http://edamontology.org/operation_3559", "term": "Ontology visualisation" } ], "input": [], "output": [ { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0850", "term": "Sequence set" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1255", "term": "Sequence features" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2353", "term": "Ontology data" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0920", "term": "Genotype/phenotype report" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_0842", "term": "Identifier" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" }, { "uri": "http://edamontology.org/topic_3053", "term": "Genetics" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript", "C#" ], "license": "CC-BY-4.0", "collectionID": [ "elixir-fr-sdp-2019", "Animal and Crop Genomics" ], "maturity": "Mature", "cost": null, "accessibility": "Restricted access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://urgi.versailles.inra.fr/gnpis/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/database/bat058", "pmid": "23959375", "pmcid": "PMC3746681", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "GnpIS: An information system to integrate genetic and genomic data from plants and fungi", "abstract": "Data integration is a key challenge for modern bioinformatics. It aims to provide biologists with tools to explore relevant data produced by different studies. Large-scale international projects can generate lots of heterogeneous and unrelated data. The challenge is to integrate this information with other publicly available data. Nucleotide sequencing throughput has been improved with new technologies; this increases the need for powerful information systems able to store, manage and explore data. GnpIS is a multispecies integrative information system dedicated to plant and fungi pests. It bridges genetic and genomic data, allowing researchers access to both genetic information (e.g. genetic maps, quantitative trait loci, markers, single nucleotide polymorphisms, germplasms and genotypes) and genomic data (e.g. genomic sequences, physical maps, genome annotation and expression data) for species of agronomical interest. GnpIS is used by both large international projects and plant science departments at the French National Institute for Agricultural Research. Here, we illustrate its use. © The Author(s) 2013. Published by Oxford University Press.", "date": "2013-12-01T00:00:00Z", "citationCount": 42, "authors": [ { "name": "Steinbach D." }, { "name": "Alaux M." }, { "name": "Amselem J." }, { "name": "Choisne N." }, { "name": "Durand S." }, { "name": "Flores R." }, { "name": "Keliet A.-O." }, { "name": "Kimmel E." }, { "name": "Lapalu N." }, { "name": "Luyten I." }, { "name": "Michotey C." }, { "name": "Mohellibi N." }, { "name": "Pommier C." }, { "name": "Reboux S." }, { "name": "Valdenaire D." }, { "name": "Verdelet D." }, { "name": "Quesneville H." } ], "journal": "Database" } }, { "doi": "10.1007/978-1-4939-6658-5_5", "pmid": "27987166", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Mining plant genomic and genetic data using the gnpis information system", "abstract": "GnpIS is an information system designed to help scientists working on plants and fungi to decipher the molecular and genetic architecture of trait variations by facilitating the navigation through genetic, genomic, and phenotypic information. The purpose of the present chapter is to illustrate how users can (1) explore datasets from phenotyping experiments in order to build new datasets for studying genotype × environment interactions in traits, (2) browse into the results of other genetic analysis data such as GWAS to generate or check working hypothesis about candidate genes or to identify important alleles and germplasms for breeding programs, and (3) explore the polymorphism in specific area of the genome using InterMine, JBrowse tools embedded in the GnpIS information system.", "date": "2017-01-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Adam-Blondon A.-F." }, { "name": "Alaux M." }, { "name": "Durand S." }, { "name": "Letellier T." }, { "name": "Merceron G." }, { "name": "Mohellibi N." }, { "name": "Pommier C." }, { "name": "Steinbach D." }, { "name": "Alfama F." }, { "name": "Amselem J." }, { "name": "Charruaud D." }, { "name": "Choisne N." }, { "name": "Flores R." }, { "name": "Guerche C." }, { "name": "Jamilloux V." }, { "name": "Kimmel E." }, { "name": "Lapalu N." }, { "name": "Loaec M." }, { "name": "Michotey C." }, { "name": "Quesneville H." } ], "journal": "Methods in Molecular Biology" } }, { "doi": "10.1038/hortres.2016.56", "pmid": "27917288", "pmcid": "PMC5120350", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Towards an open grapevine information system", "abstract": "Viticulture, like other fields of agriculture, is currently facing important challenges that will be addressed only through sustained, dedicated and coordinated research. Although the methods used in biology have evolved tremendously in recent years and now involve the routine production of large data sets of varied nature, in many domains of study, including grapevine research, there is a need to improve the findability, accessibility, interoperability and reusability (FAIR-ness) of these data. Considering the heterogeneous nature of the data produced, the transnational nature of the scientific community and the experience gained elsewhere, we have formed an open working group, in the framework of the International Grapevine Genome Program (www.vitaceae.org), to construct a coordinated federation of information systems holding grapevine data distributed around the world, providing an integrated set of interfaces supporting advanced data modeling, rich semantic integration and the next generation of data mining tools. To achieve this goal, it will be critical to develop, implement and adopt appropriate standards for data annotation and formatting. The development of this system, the GrapeIS, linking genotypes to phenotypes, and scientific research to agronomical and oeneological data, should provide new insights into grape biology, and allow the development of new varieties to meet the challenges of biotic and abiotic stress, environmental change, and consumer demand.", "date": "2016-11-23T00:00:00Z", "citationCount": 37, "authors": [ { "name": "Adam-Blondon A.-F." }, { "name": "Alaux M." }, { "name": "Pommier C." }, { "name": "Cantu D." }, { "name": "Cheng Z.-M." }, { "name": "Cramer G." }, { "name": "Davies C." }, { "name": "Delrot S." }, { "name": "Deluc L." }, { "name": "Di Gaspero G." }, { "name": "Grimplet J." }, { "name": "Fennell A." }, { "name": "Londo J." }, { "name": "Kersey P." }, { "name": "Mattivi F." }, { "name": "Naithani S." }, { "name": "Neveu P." }, { "name": "Nikolski M." }, { "name": "Pezzotti M." }, { "name": "Reisch B." }, { "name": "Topfer R." }, { "name": "Vivier M." }, { "name": "Ware D." }, { "name": "Quesneville H." } ], "journal": "Horticulture Research" } }, { "doi": "10.3835/plantgenome2015.06.0038", "pmid": "27898761", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "TransPLANT resources for triticeae genomic data", "abstract": "The genome sequences of many important Triticeae species, including bread wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), remained uncharacterized for a long time because their high repeat content, large sizes, and polyploidy. As a result of improvements in sequencing technologies and novel analyses strategies, several of these have recently been deciphered. These efforts have generated new insights into Triticeae biology and genome organization and have important implications for downstream usage by breeders, experimental biologists, and comparative genomicists. transPLANT (http://www.transplantdb.eu) is an EU-funded project aimed at constructing hardware, software, and data infrastructure for genome-scale research in the life sciences. Since the Triticeae data are intrinsically complex, heterogenous, and distributed, the transPLANT consortium has undertaken efforts to develop common data formats and tools that enable the exchange and integration of data from distributed resources. Here we present an overview of the individual Triticeae genome resources hosted by transPLANT partners, introduce the objectives of transPLANT, and outline common developments and interfaces supporting integrated data access.", "date": "2016-03-01T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Spannagl M." }, { "name": "Alaux M." }, { "name": "Lange M." }, { "name": "Bolser D.M." }, { "name": "Bader K.C." }, { "name": "Letellier T." }, { "name": "Kimmel E." }, { "name": "Flores R." }, { "name": "Pommier C." }, { "name": "Kerhornou A." }, { "name": "Walts B." }, { "name": "Nussbaumer T." }, { "name": "Grabmuller C." }, { "name": "Chen J." }, { "name": "Colmsee C." }, { "name": "Beier S." }, { "name": "Mascher M." }, { "name": "Schmutzer T." }, { "name": "Arend D." }, { "name": "Thanki A." }, { "name": "Ramirez-Gonzalez R." }, { "name": "Ayling M." }, { "name": "Ayling S." }, { "name": "Caccamo M." }, { "name": "Mayer K.F.X." }, { "name": "Scholz U." }, { "name": "Steinbach D." }, { "name": "Quesneville H." }, { "name": "Kersey P.J." } ], "journal": "Plant Genome" } } ], "credit": [ { "name": null, "email": "urgi-contact@versailles.inra.fr", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "cpommier", "additionDate": "2017-03-23T14:24:24Z", "lastUpdate": "2025-07-29T13:42:38.871501Z", "editPermission": { "type": "group", "authors": [ "urgi-contact", "animalandcropgenomics", "nfrancillon", "cmichotey" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BIGR XNAT", "description": "Imaging platform based on the open source XNAT software. It is used for sharing de-identified medical imaging data, and for data exchange in collaborative research projects. The data is served in a standardized way, with proper access control.", "homepage": "https://bigr-xnat.erasmusmc.nl", "biotoolsID": "bigr_xnat", "biotoolsCURIE": "biotools:bigr_xnat", "version": [ "1" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Deposition" }, { "uri": "http://edamontology.org/operation_3443", "term": "Image analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3468", "term": "xls" }, { "uri": "http://edamontology.org/format_3550", "term": "mhd" }, { "uri": "http://edamontology.org/format_3551", "term": "nrrd" }, { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" }, { "uri": "http://edamontology.org/format_3549", "term": "nii" } ] }, { "data": { "uri": "http://edamontology.org/data_3546", "term": "Image metadata" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3468", "term": "xls" }, { "uri": "http://edamontology.org/format_3550", "term": "mhd" }, { "uri": "http://edamontology.org/format_3551", "term": "nrrd" }, { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" }, { "uri": "http://edamontology.org/format_3549", "term": "nii" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3468", "term": "xls" }, { "uri": "http://edamontology.org/format_3550", "term": "mhd" }, { "uri": "http://edamontology.org/format_3551", "term": "nrrd" }, { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" }, { "uri": "http://edamontology.org/format_3549", "term": "nii" } ] }, { "data": { "uri": "http://edamontology.org/data_3546", "term": "Image metadata" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" }, { "uri": "http://edamontology.org/format_3468", "term": "xls" }, { "uri": "http://edamontology.org/format_3550", "term": "mhd" }, { "uri": "http://edamontology.org/format_3551", "term": "nrrd" }, { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" }, { "uri": "http://edamontology.org/format_3549", "term": "nii" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web API" ], "topic": [ { "uri": "http://edamontology.org/topic_3384", "term": "Medical imaging" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "BioMedBridges Tools" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://xnat.bigr.nl", "type": [ "Helpdesk" ], "note": null } ], "download": [], "documentation": [ { "url": "http://xnat.bigr.nl", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1186/2043-9113-5-s1-s18", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Erwin Vast", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "NRG Lab, Washington University School of Medicine", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Contributor" ], "note": null }, { "name": "Erasmus MC", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "BioMedBridges", "email": null, "url": "http://www.biomedbridges.eu", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Documentor" ], "note": null }, { "name": null, "email": null, "url": "http://xnat.bigr.nl", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Stefan Klein", "email": "s.klein@erasmusmc.nl", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "hachterberg", "additionDate": "2015-02-04T09:14:44Z", "lastUpdate": "2025-07-24T22:46:15.794823Z", "editPermission": { "type": "group", "authors": [ "korbinib" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "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": "ETENLNC", "description": "ETENLNC (End-To-End-Novel-NonCoding) is a lncRNA identification and analysis framework", "homepage": "https://github.com/EvolOMICS-TU/ETENLNC", "biotoolsID": "etenlnc", "biotoolsCURIE": "biotools:etenlnc", "version": [ "1.0" ], "otherID": [], "relation": [ { "biotoolsID": "hisat2", "type": "uses" }, { "biotoolsID": "salmon", "type": "uses" }, { "biotoolsID": "fastqc", "type": "uses" }, { "biotoolsID": "fastp", "type": "uses" }, { "biotoolsID": "stringtie", "type": "uses" }, { "biotoolsID": "gffcompare", "type": "uses" }, { "biotoolsID": "cpc2", "type": "uses" }, { "biotoolsID": "ncbi_blast_plus", "type": "uses" }, { "biotoolsID": "tximport", "type": "uses" }, { "biotoolsID": "deseq2", "type": "uses" }, { "biotoolsID": "lnctar", "type": "uses" }, { "biotoolsID": "capsule-lpi", "type": "uses" }, { "biotoolsID": "seekr", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3219", "term": "Read pre-processing" }, { "uri": "http://edamontology.org/operation_3218", "term": "Sequencing quality control" }, { "uri": "http://edamontology.org/operation_3258", "term": "Transcriptome assembly" }, { "uri": "http://edamontology.org/operation_0415", "term": "Nucleic acid feature detection" }, { "uri": "http://edamontology.org/operation_3800", "term": "RNA-Seq quantification" }, { "uri": "http://edamontology.org/operation_3223", "term": "Differential gene expression profiling" }, { "uri": "http://edamontology.org/operation_0531", "term": "Heat map generation" }, { "uri": "http://edamontology.org/operation_0278", "term": "RNA secondary structure prediction" }, { "uri": "http://edamontology.org/operation_3472", "term": "k-mer counting" }, { "uri": "http://edamontology.org/operation_0389", "term": "Protein-nucleic acid interaction analysis" }, { "uri": "http://edamontology.org/operation_3901", "term": "RNA-binding protein prediction" }, { "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": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_3112", "term": "Gene expression matrix" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] }, { "data": { "uri": "http://edamontology.org/data_1636", "term": "Heat map" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_0906", "term": "Protein interaction data" }, "format": [] } ], "note": "Run ETENLNC on paired-end raw RNA-Seq (.fastq) data", "cmd": "bash ETENLNC_docker.sh" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [], "license": "GPL-3.0", "collectionID": [], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/EvolOMICS-TU/ETENLNC", "type": [ "Repository" ], "note": "GitHub Repo" } ], "download": [ { "url": "https://zenodo.org/records/14325721?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6ImVmYTllNWJkLWE4ODUtNGM3OC05YTAxLWM4ZDk5YTljZDZjMCIsImRhdGEiOnt9LCJyYW5kb20iOiI4M2I1YjBlZDQ4MmUyZTIxNDg2YmI0YTFkMWE5MTI1OCJ9.HeB3WrsPduNzMyXjH4x5HfCgmIp4NzYv0P_11XU9lcXC_ZxEaVndP-kD0LDkxwufHVNlroeAhdK33PR51F6jnw", "type": "Biological data", "note": "Sample/demo data for ETENLNC. A detailed guide on running ETENLNC using the demo data can be found in the ETENLNC manual (supplementary to our publication).", "version": "1.0" } ], "documentation": [ { "url": "https://github.com/EvolOMICS-TU/ETENLNC", "type": [ "Command-line options" ], "note": "A detailed guide on running ETENLNC using the demo data can be found in the ETENLNC manual (supplementary to our publication)" } ], "publication": [ { "doi": "10.1016/j.compbiolchem.2024.108140", "pmid": "38996755", "pmcid": null, "type": [ "Primary" ], "version": ".0", "note": null, "metadata": { "title": "ETENLNC: An end to end lncRNA identification and analysis framework to facilitate construction of known and novel lncRNA regulatory networks", "abstract": "Long non-coding RNAs (lncRNAs) play crucial roles in the regulation of gene expression and maintenance of genomic integrity through various interactions with DNA, RNA, and proteins. The availability of large-scale sequence data from various high-throughput platforms has opened possibilities to identify, predict, and functionally annotate lncRNAs. As a result, there is a growing demand for an integrative computational framework capable of identifying known lncRNAs, predicting novel lncRNAs, and inferring the downstream regulatory interactions of lncRNAs at the genome-scale. We present ETENLNC (End-To-End-Novel-Long-NonCoding), a user-friendly, integrative, open-source, scalable, and modular computational framework for identifying and analyzing lncRNAs from raw RNA-Seq data. ETENLNC employs six stringent filtration steps to identify novel lncRNAs, performs differential expression analysis of mRNA and lncRNA transcripts, and predicts regulatory interactions between lncRNAs, mRNAs, miRNAs, and proteins. We benchmarked ETENLNC against six existing tools and optimized it for desktop workstations and high-performance computing environments using data from three different species. ETENLNC is freely available on GitHub: https://github.com/EvolOMICS-TU/ETENLNC.", "date": "2024-10-01T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Nath P." }, { "name": "Bhuyan K." }, { "name": "Bhattacharyya D.K." }, { "name": "Barah P." } ], "journal": "Computational Biology and Chemistry" } } ], "credit": [ { "name": "Pankaj Barah", "email": "barah@tezu.ernet.in", "url": "https://www.tezu.ernet.in/dmbbt/profile/34", "orcidid": "https://orcid.org/0000-0001-7039-7996", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer" ], "note": "Assistant Professor at Department of Molecular Biology and Biotechnology, Tezpur University." }, { "name": "Prangan Nath", "email": "prangannathofficial@gmai.com", "url": null, "orcidid": "https://orcid.org/0000-0002-9451-7822", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer" ], "note": null } ], "owner": "prangannath", "additionDate": "2025-07-23T10:27:57.572501Z", "lastUpdate": "2025-07-23T10:27:57.574879Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "SubtiWiki", "description": "SubtiWiki is a database for the model organism Bacillus subtilis.", "homepage": "https://subtiwiki.uni-goettingen.de/", "biotoolsID": "subtiwiki", "biotoolsCURIE": "biotools:subtiwiki", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3208", "term": "Genome visualisation" }, { "uri": "http://edamontology.org/operation_0435", "term": "Operon prediction" }, { "uri": "http://edamontology.org/operation_1781", "term": "Gene regulatory network analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_3407", "term": "Endocrinology and metabolism" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkae957", "pmid": "39441067", "pmcid": "PMC11701700", "type": [ "Primary" ], "version": "5.0", "note": null, "metadata": { "title": "A new framework for SubtiWiki, the database for the model organism Bacillus subtilis", "abstract": "Bacillus subtilis is a Gram-positive model bacterium and one of the most-studied and best understood organisms. The complex information resulting from its investigation is compiled in the database SubtiWiki (https://subtiwiki.uni-goettingen.de/v5) in an integrated and intuitive manner. To enhance the utility of SubtiWiki, we have added novel features such as a viewer to interrogate conserved genomic organization, a widget that shows mutant fitness data for all non-essential genes, and a widget showing protein structures, structure predictions and complex structures. Moreover, we have integrated metabolites as new entities. The new framework also includes a documented API, enabling programmatic access to data for computational tasks. Here we present the recent developments of SubtiWiki and the current state of the data for this organism.", "date": "2025-01-06T00:00:00Z", "citationCount": 4, "authors": [ { "name": "Elfmann C." }, { "name": "Dumann V." }, { "name": "van den Berg T." }, { "name": "Stulke J." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Jörg Stülke", "email": "jstuelk@gwdg.de", "url": null, "orcidid": "https://orcid.org/0000-0001-5881-5390", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Christoph Elfmann", "email": "christoph.elfmann@uni-goettingen.de", "url": null, "orcidid": "https://orcid.org/0000-0002-7872-8232", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": "PhD student in charge of SubtiWiki." } ], "owner": "ChristophElfmann", "additionDate": "2022-03-13T11:27:48.265908Z", "lastUpdate": "2025-07-16T13:05:53.746014Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "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": "SQANTI3", "description": "SQANTI3 constitutes the first module of the Functional IsoTranscriptomics (FIT) pipeline, which is an end-to-end strategy to perform isoform-level bioinformatics analyses. \n\nThe SQANTI3 tool is designed to enable quality control and filtering of long read-defined transcriptomes, which are often rich in artifacts and false-positive isoforms. \n\nTherefore, a good curation of the transcriptome is indispensable to proceed with FIT analysis and produce valid, biologically sound conclusions/hypothesis.", "homepage": "https://github.com/ConesaLab/SQANTI3", "biotoolsID": "sqanti3", "biotoolsCURIE": "biotools:sqanti3", "version": [ "5.5" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Spain" ], "elixirCommunity": [], "link": [ { "url": "https://github.com/ConesaLab/SQANTI3", "type": [ "Repository" ], "note": "Github repository for source code access and download" } ], "download": [ { "url": "https://github.com/ConesaLab/SQANTI3/releases", "type": "Downloads page", "note": null, "version": null }, { "url": "https://github.com/ConesaLab/SQANTI3/releases/download/v5.5/SQANTI3_v5.5.zip", "type": "Binaries", "note": "Version 5.5 download link from github", "version": "5.5" } ], "documentation": [ { "url": "https://github.com/ConesaLab/SQANTI3/wiki", "type": [ "General" ], "note": "SQANTI3 main documentation resource" }, { "url": "https://github.com/ConesaLab/SQANTI3/blob/master/CODE_OF_CONDUCT.md", "type": [ "Code of conduct" ], "note": null }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-Quality-Control", "type": [ "Command-line options" ], "note": "Command-line options and instructions for the QC submodule" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-filter", "type": [ "Command-line options" ], "note": "Command-line options and instructions for the filter submodule" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-rescue", "type": [ "Command-line options" ], "note": "Command-line options and instructions for the rescue submodule" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Dependencies-and-installation", "type": [ "Installation instructions" ], "note": "Instructions to install and use sqanti, either in docker or apptainer containers or in a linux system" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/Tutorial:-running-SQANTI3-on-an-example-dataset", "type": [ "Quick start guide" ], "note": "Basic tutorial with examples to start using SQANTI3" }, { "url": "https://github.com/ConesaLab/SQANTI3/releases", "type": [ "Release notes" ], "note": "Changelog and release notes for every version" }, { "url": "https://github.com/ConesaLab/SQANTI3?tab=readme-ov-file#how-to-cite-sqanti3", "type": [ "Citation instructions" ], "note": "Citation instructions are on the end of the Github repository's main page" }, { "url": "https://github.com/ConesaLab/SQANTI3/wiki/SQANTI3-memory-requeriments-and-paralellization", "type": [ "Other" ], "note": "Benchmarking about the resources needed to run sqanti3 with multiple cores" } ], "publication": [ { "doi": "10.1038/s41592-024-02229-2", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "5.1", "note": "Publication of SQANTI3", "metadata": { "title": "SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms", "abstract": "SQANTI3 offers a flexible tool for quality control, curation and annotation of long-read RNA sequencing data. SQANTI3 is a tool designed for the quality control, curation and annotation of long-read transcript models obtained with third-generation sequencing technologies. Leveraging its annotation framework, SQANTI3 calculates quality descriptors of transcript models, junctions and transcript ends. With this information, potential artifacts can be identified and replaced with reliable sequences. Furthermore, the integrated functional annotation feature enables subsequent functional iso-transcriptomics analyses.", "date": "2024-05-01T00:00:00Z", "citationCount": 41, "authors": [ { "name": "Pardo-Palacios F.J." }, { "name": "Arzalluz-Luque A." }, { "name": "Kondratova L." }, { "name": "Salguero P." }, { "name": "Mestre-Tomas J." }, { "name": "Amorin R." }, { "name": "Estevan-Morio E." }, { "name": "Liu T." }, { "name": "Nanni A." }, { "name": "McIntyre L." }, { "name": "Tseng E." }, { "name": "Conesa A." } ], "journal": "Nature Methods" } }, { "doi": "10.1101/gr.222976.117", "pmid": null, "pmcid": null, "type": [ "Method" ], "version": null, "note": "Original SQANTI publication", "metadata": { "title": "SQANTI: Extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification", "abstract": "High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in well-annotated mammalian species. The advances in sequencing technology have created a need for studies and tools that can characterize these novel variants. Here, we present SQANTI, an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse transcriptome using Pacific Biosciences (PacBio) long reads and illustrate how the tool is effective in characterizing and describing the composition of the full-length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an important number of the novel transcripts are technical artifacts of the sequencing approach and that SQANTI quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated transcriptome are novel combinations of existing splice sites, resulting more frequently in novel ORFs than novel UTRs, and are enriched in both general metabolic and neural-specific functions. We show that these new transcripts have a major impact in the correct quantification of transcript levels by state-of-the-art short-read-based quantification algorithms. By comparing our iso-transcriptome with public proteomics databases, we find that alternative isoforms are elusive to proteogenomics detection. SQANTI allows the user to maximize the analytical outcome of long-read technologies by providing the tools to deliver quality-evaluated and curated full-length transcriptomes.", "date": "2018-03-01T00:00:00Z", "citationCount": 256, "authors": [ { "name": "Tardaguila M." }, { "name": "De La Fuente L." }, { "name": "Marti C." }, { "name": "Pereira C." }, { "name": "Pardo-Palacios F.J." }, { "name": "Del Risco H." }, { "name": "Ferrell M." }, { "name": "Mellado M." }, { "name": "Macchietto M." }, { "name": "Verheggen K." }, { "name": "Edelmann M." }, { "name": "Ezkurdia I." }, { "name": "Vazquez J." }, { "name": "Tress M." }, { "name": "Mortazavi A." }, { "name": "Martens L." }, { "name": "Rodriguez-Navarro S." }, { "name": "Moreno-Manzano V." }, { "name": "Conesa A." } ], "journal": "Genome Research" } } ], "credit": [ { "name": "Ana Conesa", "email": "ana.conesa@csic.es", "url": null, "orcidid": "https://orcid.org/0000-0001-9597-311X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Pablo Atienza", "email": "pablo.atienza@csic.es", "url": null, "orcidid": "https://orcid.org/0009-0002-1093-693X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": "Maintainer of SQANTI3" }, { "name": "Fabián Robledo", "email": "fabian.robledo@csic.es", "url": null, "orcidid": "https://orcid.org/0009-0005-9047-3315", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": "Maintainer of SQANTI3 and ELIXIR-related contact" } ], "owner": "Fabian-RY", "additionDate": "2025-07-07T09:04:03.787249Z", "lastUpdate": "2025-07-07T09:35:33.280160Z", "editPermission": { "type": "group", "authors": [ "Fabian-RY" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MirGeneDB", "description": "MirGeneDB is a database of manually curated microRNA genes that have been validated and annotated as initially described in Fromm et al. 2015 , Fromm et al. 2020 and Fromm et al 2022. MirGeneDB 3.0 (Clarke and Hoye et al. 2024 ) includes more than 21,000 microRNA gene entries representing more than 1,700 microRNA families from 114 metazoan species. All microRNAs can be browsed, searched and downloaded.", "homepage": "http://mirgenedb.org/", "biotoolsID": "mirgen", "biotoolsCURIE": "biotools:mirgen", "version": [ "3.0" ], "otherID": [ { "value": "doi:10.25504/FAIRsharing.QXSgvF", "type": "doi", "version": "2.0" } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" }, { "uri": "http://edamontology.org/operation_0564", "term": "Sequence visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_1869", "term": "Organism identifier" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3134", "term": "Gene transcript report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] }, { "data": { "uri": "http://edamontology.org/data_0880", "term": "RNA secondary structure" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "Data retrieval: curated miRNA. Organism identifier: a specific miRNA identifier or a species for all miRNAs for that species. Gene transcript report: with metadata and visualization. RNA secondary structure: the hairpin loop of the miRNA with bases.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3495", "term": "RNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_2012", "term": "Sequence coordinates" }, "format": [ { "uri": "http://edamontology.org/format_2305", "term": "GFF" }, { "uri": "http://edamontology.org/format_3003", "term": "BED" } ] }, { "data": { "uri": "http://edamontology.org/data_3917", "term": "Count matrix" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" }, { "uri": "http://edamontology.org/topic_3299", "term": "Evolutionary biology" }, { "uri": "http://edamontology.org/topic_3500", "term": "Zoology" }, { "uri": "http://edamontology.org/topic_2815", "term": "Human biology" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "CC0-1.0", "collectionID": [ "UiO tools", "ELIXIR-NO", "ELIXIR-Norway" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Norway" ], "elixirCommunity": [], "link": [ { "url": "https://elixir.no/helpdesk", "type": [ "Helpdesk" ], "note": null } ], "download": [ { "url": "https://www.mirgenedb.org/download", "type": "Biological data", "note": "Sequence downloads for 75 species", "version": "3.0" } ], "documentation": [ { "url": "https://www.mirgenedb.org/information", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkab1101", "pmid": "34850127", "pmcid": "PMC8728216", "type": [ "Primary" ], "version": "2.1", "note": null, "metadata": { "title": "MirGeneDB 2.1: Toward a complete sampling of all major animal phyla", "abstract": "We describe an update of MirGeneDB, the manually curated microRNA gene database. Adhering to uniform and consistent criteria for microRNA annotation and nomenclature, we substantially expanded MirGeneDB with 30 additional species representing previously missing metazoan phyla such as sponges, jellyfish, rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning over ∼800 million years of animal evolution, and contains a total number of 16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new phylogenetically important species, especially those relevant for the study of whole genome duplication events, and through updating evolutionary nodes of origin for many families and genes, we were able to substantially refine our nomenclature system. All changes are traceable in the specifically developed MirGeneDB version tracker. The performance of read-pages is improved and microRNA expression matrices for all tissues and species are now also downloadable. Altogether, this update represents a significant step toward a complete sampling of all major metazoan phyla, and a widely needed foundation for comparative microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.", "date": "2022-01-07T00:00:00Z", "citationCount": 95, "authors": [ { "name": "Fromm B." }, { "name": "Hoye E." }, { "name": "Domanska D." }, { "name": "Zhong X." }, { "name": "Aparicio-Puerta E." }, { "name": "Ovchinnikov V." }, { "name": "Umu S.U." }, { "name": "Chabot P.J." }, { "name": "Kang W." }, { "name": "Aslanzadeh M." }, { "name": "Tarbier M." }, { "name": "Marmol-Sanchez E." }, { "name": "Urgese G." }, { "name": "Johansen M." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Friedlander M.R." }, { "name": "Peterson K.J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkz885", "pmid": "31598695", "pmcid": "PMC6943042", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "MirGeneDB 2.0: The metazoan microRNA complement", "abstract": "Small non-coding RNAs have gained substantial attention due to their roles in animal development and human disorders. Among them, microRNAs are special because individual gene sequences are conserved across the animal kingdom. In addition, unique and mechanistically well understood features can clearly distinguish bona fide miRNAs from the myriad other small RNAs generated by cells. However, making this distinction is not a common practice and, thus, not surprisingly, the heterogeneous quality of available miRNA complements has become a major concern in microRNA research. We addressed this by extensively expanding our curated microRNA gene database-MirGeneDB-to 45 organisms, encompassing a wide phylogenetic swath of animal evolution. By consistently annotating and naming 10,899 microRNA genes in these organisms, we show that previous microRNA annotations contained not only many false positives, but surprisingly lacked >2000 bona fide microRNAs. Indeed, curated microRNA complements of closely related organisms are very similar and can be used to reconstruct ancestral miRNA repertoires. MirGeneDB represents a robust platform for microRNA-based research, providing deeper and more significant insights into the biology and evolution of miRNAs as well as biomedical and biomarker research. MirGeneDB is publicly and freely available at http://mirgenedb.org/.", "date": "2020-01-01T00:00:00Z", "citationCount": 178, "authors": [ { "name": "Fromm B." }, { "name": "Domanska D." }, { "name": "Hoye E." }, { "name": "Ovchinnikov V." }, { "name": "Kang W." }, { "name": "Aparicio-Puerta E." }, { "name": "Johansen M." }, { "name": "Flatmark K." }, { "name": "Mathelier A." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Friedlander M.R." }, { "name": "Peterson K.J." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1146/annurev-genet-120213-092023", "pmid": "26473382", "pmcid": "PMC4743252", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "A Uniform System for the Annotation of Vertebrate microRNA Genes and the Evolution of the Human microRNAome", "abstract": "Although microRNAs (miRNAs) are among the most intensively studied molecules of the past 20 years, determining what is and what is not a miRNA has not been straightforward. Here, we present a uniform system for the annotation and nomenclature of miRNA genes. We show that less than a third of the 1,881 human miRBase entries, and only approximately 16% of the 7,095 metazoan miRBase entries, are robustly supported as miRNA genes. Furthermore, we show that the human repertoire of miRNAs has been shaped by periods of intense miRNA innovation and that mature gene products show a very different tempo and mode of sequence evolution than star products. We establish a new open access database-MirGeneDB (http://mirgenedb.org)-to catalog this set of miRNAs, which complements the efforts of miRBase but differs from it by annotating the mature versus star products and by imposing an evolutionary hierarchy upon this curated and consistently named repertoire.", "date": "2015-11-23T00:00:00Z", "citationCount": 435, "authors": [ { "name": "Fromm B." }, { "name": "Billipp T." }, { "name": "Peck L.E." }, { "name": "Johansen M." }, { "name": "Tarver J.E." }, { "name": "King B.L." }, { "name": "Newcomb J.M." }, { "name": "Sempere L.F." }, { "name": "Flatmark K." }, { "name": "Hovig E." }, { "name": "Peterson K.J." } ], "journal": "Annual Review of Genetics" } }, { "doi": "10.1093/nar/gkae1094", "pmid": "39673268", "pmcid": "PMC11701709", "type": [ "Primary" ], "version": "3.0", "note": null, "metadata": { "title": "MirGeneDB 3.0: Improved taxonomic sampling, uniform nomenclature of novel conserved microRNA families and updated covariance models", "abstract": "We present a major update of MirGeneDB (3.0), the manually curated animal microRNA gene database. Beyond moving to a new server and the creation of a computational mirror, we have expanded the database with the addition of 33 invertebrate species, including representatives of 5 previously unsampled phyla, and 6 mammal species. MirGeneDB now contains entries for 21 822 microRNA genes (5160 of these from the new species) belonging to 1743 microRNA families. The inclusion of these new species allowed us to refine both the evolutionary node of appearance of a number of microRNA genes/families, as well as MirGeneDB's phylogenetically informed nomenclature system. Updated covariance models of all microRNA families, along with all smallRNA read data are now downloadable. These enhanced annotations will allow researchers to analyze microRNA properties such as secondary structure and features of their biogenesis within a robust phylogenetic context and without the database plagued with numerous false positives and false negatives. In light of these improvements, MirGeneDB 3.0 will assume the responsibility for naming conserved novel metazoan microRNAs. MirGeneDB is part of RNAcentral and Elixir Norway and is publicly and freely available at mirgenedb.org.", "date": "2025-01-06T00:00:00Z", "citationCount": 6, "authors": [ { "name": "Clarke A.W." }, { "name": "Hoye E." }, { "name": "Hembrom A.A." }, { "name": "Paynter V.M." }, { "name": "Vinther J." }, { "name": "Wyrozemski L." }, { "name": "Biryukova I." }, { "name": "Formaggioni A." }, { "name": "Ovchinnikov V." }, { "name": "Herlyn H." }, { "name": "Pierce A." }, { "name": "Wu C." }, { "name": "Aslanzadeh M." }, { "name": "Cheneby J." }, { "name": "Martinez P." }, { "name": "Friedlander M.R." }, { "name": "Hovig E." }, { "name": "Hackenberg M." }, { "name": "Umu S.U." }, { "name": "Johansen M." }, { "name": "Peterson K.J." }, { "name": "Fromm B." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Bastian Fromm", "email": "BastianFromm@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0003-0352-3037", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer", "Support" ], "note": null }, { "name": "Kevin J. Peterson", "email": "kevin.j.peterson@dartmouth.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer" ], "note": null }, { "name": "The Norwegian Bioinformatics Platform (ELIXIR-Norway) Helpdesk", "email": "support@elixir.no", "url": "https://elixir.no/helpdesk", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Consortium", "typeRole": [ "Support" ], "note": null }, { "name": "University of Oslo", "email": null, "url": "https://www.uio.no/english/index.html", "orcidid": null, "gridid": "grid.5510.1", "rorid": "01xtthb56", "fundrefid": "10.13039/501100005366", "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "UiO", "additionDate": "2016-02-09T13:19:44Z", "lastUpdate": "2025-07-05T22:33:30.082420Z", "editPermission": { "type": "group", "authors": [ "eca008" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Pyteomics", "description": "Framework for proteomics data analysis, supporting mzML, MGF, pepXML and more.", "homepage": "https://pyteomics.readthedocs.io/", "biotoolsID": "pyteomics", "biotoolsCURIE": "biotools:pyteomics", "version": [ "4.7.5" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3767", "term": "Protein identification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0006", "term": "Data" }, "format": [ { "uri": "http://edamontology.org/format_3651", "term": "MGF" }, { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" } ] } ], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [ "Proteomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/levitsky/pyteomics", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://pypi.org/project/pyteomics/", "type": "Software package", "note": null, "version": null } ], "documentation": [ { "url": "https://pyteomics.readthedocs.io/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1007/s13361-012-0516-6", "pmid": "23292976", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Pyteomics - A python framework for exploratory data analysis and rapid software prototyping in proteomics", "abstract": "Pyteomics is a cross-platform, open-source Python library providing a rich set of tools for MS-based proteomics. It provides modules for reading LC-MS/MS data, search engine output, protein sequence databases, theoretical prediction of retention times, electrochemical properties of polypeptides, mass and m/z calculations, and sequence parsing. Pyteomics is available under Apache license; release versions are available at the Python Package Index http://pypi.python. org/pyteomics, the source code repository at http://hg.theorchromo.ru/pyteomics, documentation at http://packages.python.org/pyteomics. Pyteomics.biolccc documentation is available at http://packages.python.org/pyteomics.biolccc/. Questions on installation and usage can be addressed to pyteomics mailing list: pyteomics@googlegroups.com [Figure not available: see fulltext.] © 2013 American Society for Mass Spectrometry.", "date": "2013-02-01T00:00:00Z", "citationCount": 141, "authors": [ { "name": "Goloborodko A.A." }, { "name": "Levitsky L.I." }, { "name": "Ivanov M.V." }, { "name": "Gorshkov M.V." } ], "journal": "Journal of the American Society for Mass Spectrometry" } }, { "doi": "10.1021/acs.jproteome.8b00717", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Pyteomics 4.0: Five Years of Development of a Python Proteomics Framework", "abstract": "Many of the novel ideas that drive today's proteomic technologies are focused essentially on experimental or data-processing workflows. The latter are implemented and published in a number of ways, from custom scripts and programs, to projects built using general-purpose or specialized workflow engines; a large part of routine data processing is performed manually or with custom scripts that remain unpublished. Facilitating the development of reproducible data-processing workflows becomes essential for increasing the efficiency of proteomic research. To assist in overcoming the bioinformatics challenges in the daily practice of proteomic laboratories, 5 years ago we developed and announced Pyteomics, a freely available open-source library providing Python interfaces to proteomic data. We summarize the new functionality of Pyteomics developed during the time since its introduction.", "date": "2019-02-01T00:00:00Z", "citationCount": 117, "authors": [ { "name": "Levitsky L.I." }, { "name": "Klein J.A." }, { "name": "Ivanov M.V." }, { "name": "Gorshkov M.V." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Pyteomics Google Groups", "email": "pyteomics@googlegroups.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null }, { "name": "Issue tracker", "email": null, "url": "https://github.com/levitsky/pyteomics/issues", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "msutils_import", "additionDate": "2017-01-17T14:50:32Z", "lastUpdate": "2025-07-04T15:07:26.685242Z", "editPermission": { "type": "group", "authors": [ "proteomics.bio.tools", "levitsky" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Chopper", "description": "Rust implementation of NanoFilt+NanoLyse, both originally written in Python. This tool, intended for long read sequencing such as PacBio or ONT, filters and trims a fastq file.", "homepage": "https://github.com/wdecoster/chopper", "biotoolsID": "chopper", "biotoolsCURIE": "biotools:chopper", "version": [ "v0.10.0b" ], "otherID": [], "relation": [ { "biotoolsID": "nanopack", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3695", "term": "Data filtering" }, { "uri": "http://edamontology.org/operation_3192", "term": "Sequence trimming" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "note": null, "cmd": "gunzip -c reads.fastq.gz | chopper -q 10 -l 500 | gzip > filtered_reads.fastq.gz\nchopper -q 10 -l 500 -i reads.fastq > filtered_reads.fastq\nchopper -q 10 -l 500 -i reads.fastq.gz | gzip > filtered_reads.fastq.gz" }, { "operation": [ { "uri": "http://edamontology.org/operation_2940", "term": "Scatter plot plotting" }, { "uri": "http://edamontology.org/operation_2943", "term": "Box-Whisker plot plotting" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [ { "uri": "http://edamontology.org/format_3579", "term": "JPG" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3168", "term": "Sequencing" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [], "license": "MIT", "collectionID": [ "ONTeater" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/wdecoster/chopper", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/bioinformatics/btad311", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "NanoPack2: population-scale evaluation of long-read sequencing data", "abstract": "Increases in the cohort size in long-read sequencing projects necessitate more efficient software for quality assessment and processing of sequencing data from Oxford Nanopore Technologies and Pacific Biosciences. 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. The repositories include test data, and the tools are continuously tested using GitHub Actions and can be installed with the conda dependency manager.", "date": "2023-05-01T00:00:00Z", "citationCount": 211, "authors": [ { "name": "De Coster W." }, { "name": "Rademakers R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Wouter de Coster", "email": "decosterwouter@gmail.com", "url": "https://gigabaseorgigabyte.wordpress.com", "orcidid": "https://orcid.org/0000-0002-5248-8197", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "Keiler_Collier", "additionDate": "2025-06-18T09:20:19.874306Z", "lastUpdate": "2025-06-30T15:46:01.095401Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SILVA rRNA database", "description": "SILVA provides comprehensive, quality checked and regularly updated datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukaryota).", "homepage": "https://www.arb-silva.de", "biotoolsID": "silva", "biotoolsCURIE": "biotools:silva", "version": [], "otherID": [ { "value": "RRID:SCR_006423", "type": "rrid", "version": null } ], "relation": [ { "biotoolsID": "silvangs", "type": "usedBy" }, { "biotoolsID": "d3hub", "type": "includedIn" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0224", "term": "Query and retrieval" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1097", "term": "Sequence accession (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_1868", "term": "Taxon" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_1046", "term": "Strain name" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_1088", "term": "Article ID" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] }, { "data": { "uri": "http://edamontology.org/data_2909", "term": "Organism name" }, "format": [ { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2955", "term": "Sequence report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] }, { "data": { "uri": "http://edamontology.org/data_1383", "term": "Sequence alignment (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] }, { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] } ], "note": "The search and retrieval functions of the SILVA website can be used to build custom subsets of sequences. In addition to simple searches e.g. for accession numbers, organism names, taxonomic entities, or publication DOI/PubMed IDs, complex queries over several database fields using constraints such as sequence length or quality values are possible. The results can be sorted according to accession numbers, organism names, sequence length, sequence and alignment quality and Pintail values. The search results show accession number, organism name, sequence length, sequence quality values, taxonomic classifications, and links to view the full sequence record on SILVA and on ENA. Sequences found via search and added to download cart can be downloaded as FASTA and ARB files.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2419", "term": "Primer and probe design" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1207", "term": "nucleotide" } ] }, { "data": { "uri": "http://edamontology.org/data_1240", "term": "PCR primers" }, "format": [ { "uri": "http://edamontology.org/format_1207", "term": "nucleotide" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] }, { "data": { "uri": "http://edamontology.org/data_0850", "term": "Sequence set" }, "format": [ { "uri": "http://edamontology.org/format_2333", "term": "Binary format" } ] }, { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] }, { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] } ], "note": "The SILVA Probe Match and Evaluation Tool detects and displays all occurrences of a given probe or primer sequence in the SILVA datasets. \n\nTestPrime allows you to evaluate the performance of primer pairs by running an in silico PCR on the SILVA databases. From the results of the PCR, TestPrime computes coverages for each taxonomic group in all of the taxonomies offered by SILVA.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0492", "term": "Multiple sequence alignment" }, { "uri": "http://edamontology.org/operation_0496", "term": "Global alignment" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" }, { "uri": "http://edamontology.org/operation_0547", "term": "Phylogenetic inference (maximum likelihood and Bayesian methods)" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1383", "term": "Nucleic acid sequence alignment" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] }, { "data": { "uri": "http://edamontology.org/data_0867", "term": "Sequence alignment report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] }, { "data": { "uri": "http://edamontology.org/data_0872", "term": "Phylogenetic tree" }, "format": [ { "uri": "http://edamontology.org/format_1910", "term": "newick" } ] }, { "data": { "uri": "http://edamontology.org/data_1872", "term": "Taxonomic classification" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": "The Alignment, Classification and Tree Service (ACT) of SILVA allows to align and optionally classify sequences using the SILVA Incremental Aligner (SINA). From aligned sequences, (optionally) phylogenetic trees can be inferred using FastTree or RAxML.", "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" }, { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_3050", "term": "Biodiversity" }, { "uri": "http://edamontology.org/topic_3301", "term": "Microbiology" }, { "uri": "http://edamontology.org/topic_0632", "term": "Probes and primers" } ], "operatingSystem": [], "language": [], "license": "CC-BY-4.0", "collectionID": [ "de.NBI", "de.NBI-biodata", "DSMZ Digital Diversity" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Data" ], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [ { "url": "https://www.arb-silva.de/browser/", "type": [ "Service" ], "note": "SILVA Taxonomy Browser" }, { "url": "https://www.arb-silva.de/search/", "type": [ "Service" ], "note": "SILVA metadata search" }, { "url": "https://www.arb-silva.de/aligner/", "type": [ "Service" ], "note": "ACT: Alignment, Classification and Tree Service" }, { "url": "https://www.arb-silva.de/search/testprobe/", "type": [ "Service" ], "note": "SILVA Probe Match and Evaluation Tool" }, { "url": "https://www.arb-silva.de/search/testprime/", "type": [ "Service" ], "note": "SILVA Primer Evaluation Tool" }, { "url": "https://treeviewer.arb-silva.de/", "type": [ "Service" ], "note": "Web-based viewer for the SILVA guide trees" } ], "download": [ { "url": "https://www.arb-silva.de/download/archive/", "type": "Downloads page", "note": "SILVA dataset archive", "version": null } ], "documentation": [ { "url": "https://www.arb-silva.de/silva-license-information/", "type": [ "Terms of use" ], "note": null }, { "url": "https://www.arb-silva.de/contact/", "type": [ "Citation instructions" ], "note": null }, { "url": "https://www.arb-silva.de/documentation/", "type": [ "General" ], "note": null }, { "url": "https://www.arb-silva.de/documentation/faqs/", "type": [ "FAQ" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gks1219", "pmid": "23193283", "pmcid": "PMC3531112", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3194 778 small subunit and 288717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches. © The Author(s) 2012.", "date": "2013-01-01T00:00:00Z", "citationCount": 22633, "authors": [ { "name": "Quast C." }, { "name": "Pruesse E." }, { "name": "Yilmaz P." }, { "name": "Gerken J." }, { "name": "Schweer T." }, { "name": "Yarza P." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkt1209", "pmid": "24293649", "pmcid": "PMC3965112", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "The SILVA and \"all-species Living Tree Project (LTP)\" taxonomic frameworks", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive resource for up-to-date quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. SILVA provides a manually curated taxonomy for all three domains of life, based on representative phylogenetic trees for the small- and large-subunit rRNA genes. This article describes the improvements the SILVA taxonomy has undergone in the last 3 years. Specifically we are focusing on the curation process, the various resources used for curation and the comparison of the SILVA taxonomy with Greengenes and RDP-II taxonomies. Our comparisons not only revealed a reasonable overlap between the taxa names, but also points to significant differences in both names and numbers of taxa between the three resources. © 2013 The Author(s). Published by Oxford University Press.", "date": "2014-01-01T00:00:00Z", "citationCount": 2590, "authors": [ { "name": "Yilmaz P." }, { "name": "Parfrey L.W." }, { "name": "Yarza P." }, { "name": "Gerken J." }, { "name": "Pruesse E." }, { "name": "Quast C." }, { "name": "Schweer T." }, { "name": "Peplies J." }, { "name": "Ludwig W." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkm864", "pmid": "17947321", "pmcid": "PMC2175337", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB", "abstract": "Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs. © 2007 The Author(s).", "date": "2007-12-01T00:00:00Z", "citationCount": 5291, "authors": [ { "name": "Pruesse E." }, { "name": "Quast C." }, { "name": "Knittel K." }, { "name": "Fuchs B.M." }, { "name": "Ludwig W." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/bts252", "pmid": "22556368", "pmcid": "PMC3389763", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes", "abstract": "Motivation: In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements.Results: In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. © The Author(s) 2012. Published by Oxford University Press.", "date": "2012-07-01T00:00:00Z", "citationCount": 2408, "authors": [ { "name": "Pruesse E." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Bioinformatics" } }, { "doi": "10.1016/j.jbiotec.2017.06.1198", "pmid": "28648396", "pmcid": null, "type": [ "Review" ], "version": null, "note": null, "metadata": { "title": "25 years of serving the community with ribosomal RNA gene reference databases and tools", "abstract": "SILVA (lat. forest) is a comprehensive web resource, providing services around up to date, high-quality datasets of aligned ribosomal RNA gene (rDNA) sequences from the Bacteria, Archaea, and Eukaryota domains. SILVA dates back to the year 1991 when Dr. Wolfgang Ludwig from the Technical University Munich started the integrated software workbench ARB (lat. tree) to support high-quality phylogenetic inference and taxonomy based on the SSU and LSU rDNA marker genes. At that time, the ARB project maintained both, the sequence reference datasets and the software package for data analysis. In 2005, with the massive increase of DNA sequence data, the maintenance of the software system ARB and the corresponding rRNA databases SILVA was split between Munich and the Microbial Genomics and Bioinformatics Research Group in Bremen. ARB has been continuously developed to include new features and improve the usability of the workbench. Thousands of users worldwide appreciate the seamless integration of common analysis tools under a central graphical user interface, in combination with its versatility. The first SILVA release was deployed in February 2007 based on the EMBL-EBI/ENA release 89. Since then, full SILVA releases offering the database content in various flavours are published at least annually, complemented by intermediate web-releases where only the SILVA web dataset is updated. SILVA is the only rDNA database project worldwide where special emphasis is given to the consistent naming of clades of uncultivated (environmental) sequences, where no validly described cultivated representatives are available. Also exclusive for SILVA is the maintenance of both comprehensive aligned 16S/18S rDNA and 23S/28S rDNA sequence datasets. Furthermore, the SILVA alignments and trees were designed to include Eukaryota, another unique feature among rDNA databases. With the termination of the European Ribosomal RNA Database Project in 2007, the SILVA database has become the authoritative rDNA database project for Europe. The application spectrum of ARB and SILVA ranges from biodiversity analysis, medical diagnostics, to biotechnology and quality control for academia and industry.", "date": "2017-11-10T00:00:00Z", "citationCount": 635, "authors": [ { "name": "Glockner F.O." }, { "name": "Yilmaz P." }, { "name": "Quast C." }, { "name": "Gerken J." }, { "name": "Beccati A." }, { "name": "Ciuprina A." }, { "name": "Bruns G." }, { "name": "Yarza P." }, { "name": "Peplies J." }, { "name": "Westram R." }, { "name": "Ludwig W." } ], "journal": "Journal of Biotechnology" } }, { "doi": "10.1186/s12859-017-1841-3", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "SILVA tree viewer: Interactive web browsing of the SILVA phylogenetic guide trees", "abstract": "Background: Phylogenetic trees are an important tool to study the evolutionary relationships among organisms. The huge amount of available taxa poses difficulties in their interactive visualization. This hampers the interaction with the users to provide feedback for the further improvement of the taxonomic framework. Results: The SILVA Tree Viewer is a web application designed for visualizing large phylogenetic trees without requiring the download of any software tool or data files. The SILVA Tree Viewer is based on Web Geographic Information Systems (Web-GIS) technology with a PostgreSQL backend. It enables zoom and pan functionalities similar to Google Maps. The SILVA Tree Viewer enables access to two phylogenetic (guide) trees provided by the SILVA database: the SSU Ref NR99 inferred from high-quality, full-length small subunit sequences, clustered at 99% sequence identity and the LSU Ref inferred from high-quality, full-length large subunit sequences. Conclusions: The Tree Viewer provides tree navigation, search and browse tools as well as an interactive feedback system to collect any kinds of requests ranging from taxonomy to data curation and improving the tool itself.", "date": "2017-09-30T00:00:00Z", "citationCount": 29, "authors": [ { "name": "Beccati A." }, { "name": "Gerken J." }, { "name": "Quast C." }, { "name": "Yilmaz P." }, { "name": "Glockner F.O." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures", "email": "hub@dsmz.de", "url": "https://www.dsmz.de", "orcidid": null, "gridid": "grid.420081.f", "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "SILVA Team", "email": "contact@arb-silva.de", "url": "https://www.arb-silva.de/contact/team/", "orcidid": null, "gridid": "grid.507782.f", "rorid": "027z9pz32", "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "silva", "additionDate": "2016-09-30T15:59:05Z", "lastUpdate": "2025-06-30T13:26:42.882897Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "SILVAngs", "description": "SILVAngs is a data analysis service for ribosomal RNA gene (rDNA) amplicon reads from high-throughput sequencing (next-generation sequencing (NGS)) approaches based on an automatic software pipeline. It uses the SILVA rDNA databases, taxonomies, and alignments as a reference. It facilitates the classification of rDNA reads and provides a wealth of results (tables, graphs and sequence files) for download.", "homepage": "https://ngs.arb-silva.de", "biotoolsID": "silvangs", "biotoolsCURIE": "biotools:silvangs", "version": [ "1.9.10" ], "otherID": [], "relation": [ { "biotoolsID": "silva", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" }, { "uri": "http://edamontology.org/operation_2478", "term": "Nucleic acid sequence analysis" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" }, { "uri": "http://edamontology.org/operation_2428", "term": "Validation" }, { "uri": "http://edamontology.org/operation_0291", "term": "Sequence clustering" }, { "uri": "http://edamontology.org/operation_0292", "term": "Sequence alignment" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2082", "term": "Matrix" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] }, { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] }, { "data": { "uri": "http://edamontology.org/data_1246", "term": "Sequence cluster (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] }, { "data": { "uri": "http://edamontology.org/data_2977", "term": "Nucleic acid sequence" }, "format": [ { "uri": "http://edamontology.org/format_3830", "term": "ARB" }, { "uri": "http://edamontology.org/format_1984", "term": "FASTA-aln" } ] } ], "note": "The pipeline accepts input data in Multi-Fasta format with each input file representing one sample. Samples that belong to one project (a transect, timeseries etc.) should be uploaded as a single SILVAngs project.", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3050", "term": "Biodiversity" }, { "uri": "http://edamontology.org/topic_0637", "term": "Taxonomy" }, { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [ "de.NBI", "de.NBI-biodata", "DSMZ Digital Diversity" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": null, "elixirPlatform": [ "Data" ], "elixirNode": [ "Germany" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://www.arb-silva.de/fileadmin/silva_databases/sngs/SILVAngs_User_Guide.pdf", "type": [ "User manual" ], "note": null }, { "url": "https://www.arb-silva.de/documentation/silvangs/userfaq/", "type": [ "FAQ" ], "note": null }, { "url": "https://www.arb-silva.de/footer/sngs-termsofuse", "type": [ "Terms of use" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gks1219", "pmid": "23193283", "pmcid": "PMC3531112", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3194 778 small subunit and 288717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches. © The Author(s) 2012.", "date": "2013-01-01T00:00:00Z", "citationCount": 22633, "authors": [ { "name": "Quast C." }, { "name": "Pruesse E." }, { "name": "Yilmaz P." }, { "name": "Gerken J." }, { "name": "Schweer T." }, { "name": "Yarza P." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkt1209", "pmid": "24293649", "pmcid": "PMC3965112", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The SILVA and \"all-species Living Tree Project (LTP)\" taxonomic frameworks", "abstract": "SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive resource for up-to-date quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. SILVA provides a manually curated taxonomy for all three domains of life, based on representative phylogenetic trees for the small- and large-subunit rRNA genes. This article describes the improvements the SILVA taxonomy has undergone in the last 3 years. Specifically we are focusing on the curation process, the various resources used for curation and the comparison of the SILVA taxonomy with Greengenes and RDP-II taxonomies. Our comparisons not only revealed a reasonable overlap between the taxa names, but also points to significant differences in both names and numbers of taxa between the three resources. © 2013 The Author(s). Published by Oxford University Press.", "date": "2014-01-01T00:00:00Z", "citationCount": 2590, "authors": [ { "name": "Yilmaz P." }, { "name": "Parfrey L.W." }, { "name": "Yarza P." }, { "name": "Gerken J." }, { "name": "Pruesse E." }, { "name": "Quast C." }, { "name": "Schweer T." }, { "name": "Peplies J." }, { "name": "Ludwig W." }, { "name": "Glockner F.O." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/bioinformatics/bts252", "pmid": "22556368", "pmcid": "PMC3389763", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes", "abstract": "Motivation: In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements.Results: In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. © The Author(s) 2012. Published by Oxford University Press.", "date": "2012-07-01T00:00:00Z", "citationCount": 2408, "authors": [ { "name": "Pruesse E." }, { "name": "Peplies J." }, { "name": "Glockner F.O." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "SILVA Team", "email": "ngs-contact@arb-silva.de", "url": "https://www.arb-silva.de/contact/team/", "orcidid": null, "gridid": "grid.507782.f", "rorid": "027z9pz32", "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures", "email": "hub@dsmz.de", "url": "https://www.dsmz.de", "orcidid": null, "gridid": "grid.420081.f", "rorid": "02tyer376", "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null } ], "owner": "silva", "additionDate": "2016-09-30T07:30:11Z", "lastUpdate": "2025-06-30T13:26:39.251875Z", "editPermission": { "type": "group", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "The MINERVA Platform", "description": "The MINERVA (Molecular Interaction NEtwoRk VisuAlization) platform is a standalone webserver for visualization, exploration and management of molecular networks encoded in SBGN-compliant format, including files produced using CellDesigner or SBGN editors. Visualization of uploaded networks generated by the platform is accessible via a web browser to all viewers with the weblink to the resource.\n\nThe MINERVA Platform is a webservice using the Java Server Faces 2 technology. The server side, including data parsing, integration, annotation and verification, is implemented in Java. The platform uses the Postgres SQL database for data storage and the Hibernate framework as a middle layer between web server and database. The user web-interface is generated using React.js. The displayed content is visualized by OpenLayers API, dedicated JavaScript and CSS.", "homepage": "https://minerva.uni.lu", "biotoolsID": "MINERVA_Platform", "biotoolsCURIE": "biotools:MINERVA_Platform", "version": [ "13.1.3", "13.2.0", "14.0.13", "15.0.3", "16.4.0", "17.1.3", "18.1.1" ], "otherID": [], "relation": [ { "biotoolsID": "pathvisio", "type": "uses" }, { "biotoolsID": "sbgn", "type": "uses" }, { "biotoolsID": "libsbml", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3926", "term": "Pathway visualisation" } ], "input": [], "output": [], "note": "Visualise systems biology diagrams online, on a standalone web server", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0571", "term": "Expression data visualisation" } ], "input": [], "output": [], "note": "Visualise omics data from multiple datasets on top of the diagrams", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3434", "term": "Conversion" } ], "input": [], "output": [], "note": "Convert between main systems biology layout formats: CellDeslgners SBML, SBML layout+render, SBGN-ML, GPML", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2426", "term": "Modelling and simulation" } ], "input": [], "output": [], "note": "Use MINERVA API to access systems biology formats for modelling", "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_3391", "term": "Omics" }, { "uri": "http://edamontology.org/topic_3342", "term": "Translational medicine" }, { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" } ], "operatingSystem": [], "language": [], "license": "AGPL-3.0", "collectionID": [ "ELIXIR-LU", "LCSB" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Luxembourg" ], "elixirCommunity": [], "link": [ { "url": "https://gitlab.lcsb.uni.lu/minerva/core/", "type": [ "Repository" ], "note": "GiLab repository for core functionalities (data and format handling, service stability, API access)" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/core/-/issues", "type": [ "Issue tracker" ], "note": "Issue tracker for core functionalities (data and format handling, service stability, API access)" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/frontend", "type": [ "Repository" ], "note": "GiLab repository for frontend functionalities" }, { "url": "https://gitlab.lcsb.uni.lu/minerva/frontend/-/issues", "type": [ "Issue tracker" ], "note": "Issue tracker for frontend functionalities" } ], "download": [ { "url": "https://minerva.pages.uni.lu/doc/install/", "type": "Other", "note": "Installation instructions, including debian package, virtual machine images and docker containers.", "version": "13.1.3 - 18.1.1" } ], "documentation": [ { "url": "https://minerva.uni.lu", "type": [ "Quick start guide", "Release notes", "User manual", "API documentation", "Citation instructions", "Terms of use" ], "note": null } ], "publication": [ { "doi": "10.1038/npjsba.2016.20", "pmid": "28725475", "pmcid": "PMC5516855", "type": [ "Primary" ], "version": "10.0", "note": null, "metadata": { "title": "MINERVA—A platform for visualization and curation of molecular interaction networks", "abstract": "Our growing knowledge about various molecular mechanisms is becoming increasingly more structured and accessible. Different repositories of molecular interactions and available literature enable construction of focused and high-quality molecular interaction networks. Novel tools for curation and exploration of such networks are needed, in order to foster the development of a systems biology environment. In particular, solutions for visualization, annotation and data cross-linking will facilitate usage of network-encoded knowledge in biomedical research. To this end we developed the MINERVA (Molecular Interaction NEtwoRks VisuAlization) platform, a standalone webservice supporting curation, annotation and visualization of molecular interaction networks in Systems Biology Graphical Notation (SBGN)-compliant format. MINERVA provides automated content annotation and verification for improved quality control. The end users can explore and interact with hosted networks, and provide direct feedback to content curators. MINERVA enables mapping drug targets or overlaying experimental data on the visualized networks. Extensive export functions enable downloading areas of the visualized networks as SBGN-compliant models for efficient reuse of hosted networks. The software is available under Affero GPL 3.0 as a Virtual Machine snapshot, Debian package and Docker instance at http://r3lab.uni.lu/web/minerva-website/. We believe that MINERVA is an important contribution to systems biology community, as its architecture enables set-up of locally or globally accessible SBGN-oriented repositories of molecular interaction networks. Its functionalities allow overlay of multiple information layers, facilitating exploration of content and interpretation of data. Moreover, annotation and verification workflows of MINERVA improve the efficiency of curation of networks, allowing life-science researchers to better engage in development and use of biomedical knowledge repositories.", "date": "2016-01-01T00:00:00Z", "citationCount": 65, "authors": [ { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Satagopam V." }, { "name": "Gebel S." }, { "name": "Mazein A." }, { "name": "Kuzma M." }, { "name": "Zorzan S." }, { "name": "McGee F." }, { "name": "Otjacques B." }, { "name": "Balling R." }, { "name": "Schneider R." } ], "journal": "npj Systems Biology and Applications" } }, { "doi": "10.1093/bioinformatics/btz286", "pmid": "31074494", "pmcid": "PMC6821317", "type": [ "Primary" ], "version": "12.2.3", "note": null, "metadata": { "title": "MINERVA API and plugins: Opening molecular network analysis and visualization to the community", "abstract": "Summary: The complexity of molecular networks makes them difficult to navigate and interpret, creating a need for specialized software. MINERVA is a web platform for visualization, exploration and management of molecular networks. Here, we introduce an extension to MINERVA architecture that greatly facilitates the access and use of the stored molecular network data. It allows to incorporate such data in analytical pipelines via a programmatic access interface, and to extend the platform's visual exploration and analytics functionality via plugin architecture. This is possible for any molecular network hosted by the MINERVA platform encoded in well-recognized systems biology formats. To showcase the possibilities of the plugin architecture, we have developed several plugins extending the MINERVA core functionalities. In the article, we demonstrate the plugins for interactive tree traversal of molecular networks, for enrichment analysis and for mapping and visualization of known disease variants or known adverse drug reactions to molecules in the network. Availability and implementation: Plugins developed and maintained by the MINERVA team are available under the AGPL v3 license at https://git-r3lab.uni.lu/minerva/plugins/. The MINERVA API and plugin documentation is available at https://minerva-web.lcsb.uni.lu.", "date": "2019-11-01T00:00:00Z", "citationCount": 25, "authors": [ { "name": "Hoksza D." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Smula E." }, { "name": "Schneider R." } ], "journal": "Bioinformatics" } }, { "doi": "10.1093/bib/bbz067", "pmid": "31273380", "pmcid": "PMC7373180", "type": [ "Primary" ], "version": "13.1.1", "note": null, "metadata": { "title": "Closing the gap between formats for storing layout information in systems biology", "abstract": "The understanding of complex biological networks often relies on both a dedicated layout and a topology. Currently, there are three major competing layout-aware systems biology formats, but there are no software tools or software libraries supporting all of them. This complicates the management of molecular network layouts and hinders their reuse and extension. In this paper, we present a high-level overview of the layout formats in systems biology, focusing on their commonalities and differences, review their support in existing software tools, libraries and repositories and finally introduce a new conversion module within the MINERVA platform. The module is available via a REST API and offers, besides the ability to convert between layout-aware systems biology formats, the possibility to export layouts into several graphical formats. The module enables conversion of very large networks with thousands of elements, such as disease maps or metabolic reconstructions, rendering it widely applicable in systems biology.", "date": "2019-07-10T00:00:00Z", "citationCount": 17, "authors": [ { "name": "Hoksza D." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Hasenauer J." }, { "name": "Schneider R." } ], "journal": "Briefings in Bioinformatics" } }, { "doi": "10.1089/big.2015.0057", "pmid": "27441714", "pmcid": "PMC4932659", "type": [ "Usage" ], "version": "10.0", "note": null, "metadata": { "title": "Integration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases", "abstract": "Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services - tranSMART, a Galaxy Server, and a MINERVA platform - are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and disease-related mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data.", "date": "2016-06-01T00:00:00Z", "citationCount": 39, "authors": [ { "name": "Satagopam V." }, { "name": "Gu W." }, { "name": "Eifes S." }, { "name": "Gawron P." }, { "name": "Ostaszewski M." }, { "name": "Gebel S." }, { "name": "Barbosa-Silva A." }, { "name": "Balling R." }, { "name": "Schneider R." } ], "journal": "Big Data" } }, { "doi": "10.1016/j.envpol.2019.04.005", "pmid": "30991279", "pmcid": null, "type": [], "version": "13.1.1", "note": null, "metadata": { "title": "Genes associated with Parkinson's disease respond to increasing polychlorinated biphenyl levels in the blood of healthy females", "abstract": "Polychlorinated biphenyls (PCBs) are a class of widespread environmental pollutants, commonly found in human blood, that have been suggested to be linked to the occurrence of sporadic Parkinson's disease (PD). It has been reported that some non-coplanar PCBs accumulate in the brains of female PD patients. To improve our understanding of the association between PCB exposure and PD risk we have applied whole transcriptome gene expression analysis in blood cells from 594 PCB-exposed subjects (369 female, 225 male). Interestingly, we observe that in females, blood levels of non-coplanar PCBs appear to be associated with expression levels of PD-specific genes. However, no such association was detected in males. Among the 131 PD-specific genes affected, 39 have been shown to display similar changes in expression levels in the substantia nigra of deceased PD patients. Especially among the down-regulated genes, transcripts of genes involved in neurotransmitter vesicle-related functions were predominant. Capsule: Plasma PCB levels are associated with gene expression changes in females only, resulting in brain-related genes changing in blood cells of healthy individuals exposed to PCBs.", "date": "2019-07-01T00:00:00Z", "citationCount": 5, "authors": [ { "name": "Bohler S." }, { "name": "Krauskopf J." }, { "name": "Espin-Perez A." }, { "name": "Gebel S." }, { "name": "Palli D." }, { "name": "Rantakokko P." }, { "name": "Kiviranta H." }, { "name": "Kyrtopoulos S.A." }, { "name": "Balling R." }, { "name": "Kleinjans J." } ], "journal": "Environmental Pollution" } } ], "credit": [], "owner": "mjostaszewski", "additionDate": "2019-08-26T14:34:55Z", "lastUpdate": "2025-06-26T13:15:59.673112Z", "editPermission": { "type": "group", "authors": [ "sascha.herzinger" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "AutoDock Vina", "description": "AutoDock Vina is a new open-source program for drug discovery, molecular docking and virtual screening, offering multi-core capability, high performance and enhanced accuracy and ease of use.", "homepage": "http://vina.scripps.edu/", "biotoolsID": "autodock_vina", "biotoolsCURIE": "biotools:autodock_vina", "version": [ "1.1.2" ], "otherID": [ { "value": "RRID:SCR_011958", "type": "rrid", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0478", "term": "Molecular docking" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_3336", "term": "Drug discovery" }, { "uri": "http://edamontology.org/topic_2275", "term": "Molecular modelling" }, { "uri": "http://edamontology.org/topic_2275", "term": "Molecular docking" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "C++" ], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://www.mybiosoftware.com/autodock-vina-1-1-2-molecular-docking-virtual-screening-program.html", "type": [ "Software catalogue" ], "note": null } ], "download": [], "documentation": [ { "url": "http://vina.scripps.edu/manual.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1002/jcc.21334", "pmid": "19499576", "pmcid": "PMC3041641", "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": null, "email": null, "url": "http://olegtrott.com/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "mbs_import", "additionDate": "2017-12-18T00:03:45Z", "lastUpdate": "2025-06-22T11:35:04.906923Z", "editPermission": { "type": "group", "authors": [ "ragibsiddique" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Cytoscape Web", "description": "An online implementation of Cytoscape Desktop that captures its interface and key visualization functionality while providing integration with web tools and databases.", "homepage": "https://web.cytoscape.org/", "biotoolsID": "cytoscape_web", "biotoolsCURIE": "biotools:cytoscape_web", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_1812", "term": "Loading" }, { "uri": "http://edamontology.org/operation_0276", "term": "Protein interaction network analysis" }, { "uri": "http://edamontology.org/operation_0277", "term": "Pathway or network comparison" }, { "uri": "http://edamontology.org/operation_3083", "term": "Pathway or network visualisation" }, { "uri": "http://edamontology.org/operation_3439", "term": "Pathway or network prediction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" }, { "uri": "http://edamontology.org/topic_3382", "term": "Imaging" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript" ], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://cytoscape-web.readthedocs.io/en/latest/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkaf365", "pmid": "40308211", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": "Gary D. Bader", "email": "gary.bader@utoronto.ca", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "garybader", "additionDate": "2017-04-21T12:12:09Z", "lastUpdate": "2025-06-19T13:28:13.117454Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DeepSig", "description": "Prediction of secretory signal peptides in protein sequences", "homepage": "https://busca.biocomp.unibo.it/deepsig/", "biotoolsID": "deepsig", "biotoolsCURIE": "biotools:deepsig", "version": [ "1.2.5" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0418", "term": "Protein signal peptide detection" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_3510", "term": "Protein sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0123", "term": "Protein properties" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python", "C++" ], "license": "GPL-3.0", "collectionID": [ "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [ { "url": "https://github.com/BolognaBiocomp/deepsig", "type": "Source code", "note": null, "version": "1.2.5" }, { "url": "https://hub.docker.com/r/bolognabiocomp/deepsig", "type": "Container file", "note": null, "version": "1.2.5" } ], "documentation": [ { "url": "https://github.com/BolognaBiocomp/deepsig", "type": [ "Command-line options" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btx818", "pmid": "29280997", "pmcid": "PMC5946842", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "DeepSig: Deep learning improves signal peptide detection in proteins", "abstract": "Motivation The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Results Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. Availability and implementation DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website.", "date": "2018-05-15T00:00:00Z", "citationCount": 96, "authors": [ { "name": "Savojardo C." }, { "name": "Martelli P.L." }, { "name": "Fariselli P." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "http://biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Primary contact" ], "note": null }, { "name": "Pier Luigi Martelli", "email": "pierluigi.martelli@unibo.it", "url": "http://biocomp.unibo.it", "orcidid": "https://orcid.org/0000-0002-0274-5669", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2018-05-28T14:50:09Z", "lastUpdate": "2025-06-19T11:55:09.017105Z", "editPermission": { "type": "group", "authors": [ "savo", "ELIXIR-ITA-BOLOGNA" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "QIIME 2", "description": "QIIME 2 is an AI-ready microbiome multi-omics data science platform that is trusted, free, open source, extensible, and community developed and supported bioinformatics.", "homepage": "https://qiime2.org", "biotoolsID": "qiime2", "biotoolsCURIE": "biotools:qiime2", "version": [ "2.0" ], "otherID": [], "relation": [ { "biotoolsID": "qiime", "type": "isNewVersionOf" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3933", "term": "Demultiplexing" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Suite", "Command-line tool", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" }, { "uri": "http://edamontology.org/topic_3941", "term": "Metatranscriptomics" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [ "Galaxy" ], "link": [ { "url": "https://github.com/qiime2", "type": [ "Repository" ], "note": null }, { "url": "https://library.qiime2.org", "type": [ "Software catalogue" ], "note": null }, { "url": "https://forum.qiime2.org", "type": [ "Discussion forum" ], "note": null }, { "url": "https://view.qiime2.org", "type": [ "Other" ], "note": "Site for viewing and interacting with QIIME 2 results." } ], "download": [], "documentation": [ { "url": "https://amplicon-docs.qiime2.org", "type": [ "General" ], "note": "User documentation for amplicon analysis, oriented to new users." }, { "url": "https://moshpit.qiime2.org", "type": [ "Installation instructions" ], "note": "User documentation for metagenome analysis, oriented to new users." }, { "url": "https://use.qiime2.org", "type": [ "User manual" ], "note": "User documentation, oriented toward power users." }, { "url": "https://develop.qiime2.org", "type": [ "API documentation" ], "note": "Developer documentation, including a plugin development tutorial." }, { "url": "https://library.qiime2.org/books", "type": [ "Other" ], "note": "The QIIME 2 Library Stacks: a resource for discovering relevant documentation." } ], "publication": [ { "doi": "10.1038/s41587-019-0209-9", "pmid": "31341288", "pmcid": "PMC7015180", "type": [ "Primary" ], "version": "2.0", "note": null, "metadata": { "title": "Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2", "abstract": "", "date": "2019-08-01T00:00:00Z", "citationCount": 14289, "authors": [ { "name": "Bolyen E." }, { "name": "Rideout J.R." }, { "name": "Dillon M.R." }, { "name": "Bokulich N.A." }, { "name": "Abnet C.C." }, { "name": "Al-Ghalith G.A." }, { "name": "Alexander H." }, { "name": "Alm E.J." }, { "name": "Arumugam M." }, { "name": "Asnicar F." }, { "name": "Bai Y." }, { "name": "Bisanz J.E." }, { "name": "Bittinger K." }, { "name": "Brejnrod A." }, { "name": "Brislawn C.J." }, { "name": "Brown C.T." }, { "name": "Callahan B.J." }, { "name": "Caraballo-Rodriguez A.M." }, { "name": "Chase J." }, { "name": "Cope E.K." }, { "name": "Da Silva R." }, { "name": "Diener C." }, { "name": "Dorrestein P.C." }, { "name": "Douglas G.M." }, { "name": "Durall D.M." }, { "name": "Duvallet C." }, { "name": "Edwardson C.F." }, { "name": "Ernst M." }, { "name": "Estaki M." }, { "name": "Fouquier J." }, { "name": "Gauglitz J.M." }, { "name": "Gibbons S.M." }, { "name": "Gibson D.L." }, { "name": "Gonzalez A." }, { "name": "Gorlick K." }, { "name": "Guo J." }, { "name": "Hillmann B." }, { "name": "Holmes S." }, { "name": "Holste H." }, { "name": "Huttenhower C." }, { "name": "Huttley G.A." }, { "name": "Janssen S." }, { "name": "Jarmusch A.K." }, { "name": "Jiang L." }, { "name": "Kaehler B.D." }, { "name": "Kang K.B." }, { "name": "Keefe C.R." }, { "name": "Keim P." }, { "name": "Kelley S.T." }, { "name": "Knights D." }, { "name": "Koester I." }, { "name": "Kosciolek T." }, { "name": "Kreps J." }, { "name": "Langille M.G.I." }, { "name": "Lee J." }, { "name": "Ley R." }, { "name": "Liu Y.-X." }, { "name": "Loftfield E." }, { "name": "Lozupone C." }, { "name": "Maher M." }, { "name": "Marotz C." }, { "name": "Martin B.D." }, { "name": "McDonald D." }, { "name": "McIver L.J." }, { "name": "Melnik A.V." }, { "name": "Metcalf J.L." }, { "name": "Morgan S.C." }, { "name": "Morton J.T." }, { "name": "Naimey A.T." }, { "name": "Navas-Molina J.A." }, { "name": "Nothias L.F." }, { "name": "Orchanian S.B." }, { "name": "Pearson T." }, { "name": "Peoples S.L." }, { "name": "Petras D." }, { "name": "Preuss M.L." }, { "name": "Pruesse E." }, { "name": "Rasmussen L.B." }, { "name": "Rivers A." }, { "name": "Robeson M.S." }, { "name": "Rosenthal P." }, { "name": "Segata N." }, { "name": "Shaffer M." }, { "name": "Shiffer A." }, { "name": "Sinha R." }, { "name": "Song S.J." }, { "name": "Spear J.R." }, { "name": "Swafford A.D." }, { "name": "Thompson L.R." }, { "name": "Torres P.J." }, { "name": "Trinh P." }, { "name": "Tripathi A." }, { "name": "Turnbaugh P.J." }, { "name": "Ul-Hasan S." }, { "name": "van der Hooft J.J.J." }, { "name": "Vargas F." }, { "name": "Vazquez-Baeza Y." }, { "name": "Vogtmann E." }, { "name": "von Hippel M." }, { "name": "Walters W." }, { "name": "Wan Y." }, { "name": "Wang M." }, { "name": "Warren J." }, { "name": "Weber K.C." }, { "name": "Williamson C.H.D." }, { "name": "Willis A.D." }, { "name": "Xu Z.Z." }, { "name": "Zaneveld J.R." }, { "name": "Zhang Y." }, { "name": "Zhu Q." }, { "name": "Knight R." }, { "name": "Caporaso J.G." } ], "journal": "Nature Biotechnology" } } ], "credit": [ { "name": "Greg Caporaso", "email": "greg.caporaso@nau.edu", "url": "https://cap-lab.bio", "orcidid": "https://orcid.org/0000-0002-8865-1670", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Primary contact" ], "note": null } ], "owner": "gregcaporaso", "additionDate": "2021-05-27T09:02:10Z", "lastUpdate": "2025-06-18T21:00:46.185472Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "quickmerge", "description": "Quickmerge is a program that uses complementary information from genomes assembled with long reads in order to improve contiguity, and works with assemblies derived from both Pacific Biosciences or Oxford Nanopore. Quickmerge will even work with hybrid assemblies made by combining long reads and Illumina short reads.", "homepage": "https://github.com/mahulchak/quickmerge", "biotoolsID": "quickmerge", "biotoolsCURIE": "biotools:quickmerge", "version": [ "v.0.3" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0525", "term": "Genome assembly" }, { "uri": "http://edamontology.org/operation_3216", "term": "Scaffolding" }, { "uri": "http://edamontology.org/operation_0524", "term": "De-novo assembly" }, { "uri": "http://edamontology.org/operation_3196", "term": "Genotyping" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": "Runs whole merge process on an input assembly.\nAssembly 2 will be used to fill gaps in assembly 1.", "cmd": "merge_wrapper.py -pre output_prefix assembly_1.fa assembly_2.fa" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3175", "term": "Structural variation" }, { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/topic_2885", "term": "DNA polymorphism" }, { "uri": "http://edamontology.org/topic_3673", "term": "Whole genome sequencing" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "C++", "C" ], "license": "GPL-3.0", "collectionID": [ "ONTeater" ], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/mahulchak/quickmerge/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/mahulchak/quickmerge", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1534/g3.118.200162", "pmid": "30018084", "pmcid": "PMC6169397", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Rapid low-cost assembly of the drosophila melanogaster reference genome using low-coverage, long-read sequencing", "abstract": "Accurate and comprehensive characterization of genetic variation is essential for deciphering the genetic basis of diseases and other phenotypes. A vast amount of genetic variation stems from largescale sequence changes arising from the duplication, deletion, inversion, and translocation of sequences. In the past 10 years, high-throughput short reads have greatly expanded our ability to assay sequence variation due to single nucleotide polymorphisms. However, a recent de novo assembly of a second Drosophila melanogaster reference genome has revealed that short read genotyping methods miss hundreds of structural variants, including those affecting phenotypes. While genomes assembled using highcoverage long reads can achieve high levels of contiguity and completeness, concerns about cost, errors, and low yield have limited widespread adoption of such sequencing approaches. Here we resequenced the reference strain of D. melanogaster (ISO1) on a single Oxford Nanopore MinION flow cell run for 24 hr. Using only reads longer than 1 kb or with at least 30x coverage, we assembled a highly contiguous de novo genome. The addition of inexpensive paired reads and subsequent scaffolding using an optical map technology achieved an assembly with completeness and contiguity comparable to the D. melanogaster reference assembly. Comparison of our assembly to the reference assembly of ISO1 uncovered a number of structural variants (SVs), including novel LTR transposable element insertions and duplications affecting genes with developmental, behavioral, and metabolic functions. Collectively, these SVs provide a snapshot of the dynamics of genome evolution. Furthermore, our assembly and comparison to the D. melanogaster reference genome demonstrates that high-quality de novo assembly of reference genomes and comprehensive variant discovery using such assemblies are now possible by a single lab for under $1,000 (USD).", "date": "2018-10-01T00:00:00Z", "citationCount": 70, "authors": [ { "name": "Solares E.A." }, { "name": "Chakraborty M." }, { "name": "Miller D.E." }, { "name": "Kalsow S." }, { "name": "Hall K." }, { "name": "Perera A.G." }, { "name": "Emerson J.J." }, { "name": "Scott Hawley R." } ], "journal": "G3: Genes, Genomes, Genetics" } } ], "credit": [ { "name": "Mahul Chakraborty", "email": null, "url": "https://mahulchakraborty.wordpress.com/", "orcidid": "https://orcid.org/0000-0003-2414-9187", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "Kigaard", "additionDate": "2021-05-27T09:04:45Z", "lastUpdate": "2025-06-18T12:17:20.983962Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-CZ", "Keiler_Collier" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SKM", "description": "Stress Knowledge Map: A compilation of knowledge on mechanisms underlying responses of plants to stress, the so called stress signalling network.", "homepage": "https://skm.nib.si/", "biotoolsID": "skm", "biotoolsCURIE": "biotools:skm", "version": [], "otherID": [], "relation": [ { "biotoolsID": "gomapman", "type": "uses" }, { "biotoolsID": "newt-ve", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2299", "term": "Gene name" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [ { "uri": "http://edamontology.org/format_3464", "term": "JSON" }, { "uri": "http://edamontology.org/format_3619", "term": "sif" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" } ], "input": [], "output": [ { "data": { "uri": "http://edamontology.org/data_0950", "term": "Mathematical model" }, "format": [ { "uri": "http://edamontology.org/format_2585", "term": "SBML" }, { "uri": "http://edamontology.org/format_3692", "term": "SBGN-ML" }, { "uri": "http://edamontology.org/format_3619", "term": "sif" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_2259", "term": "Systems biology" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plant biology" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [ "ELIXIR-SI", "Plant Systems Biology" ], "maturity": "Emerging", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Slovenia" ], "elixirCommunity": [ "Plant Sciences" ], "link": [ { "url": "https://skm.nib.si/contact", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [ { "url": "https://skm.nib.si/documentation", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1016/j.xplc.2024.100920", "pmid": "38616489", "pmcid": null, "type": [ "Primary" ], "version": null, "note": "Stress Knowledge Map: A knowledge graph resource for systems biology analysis of plant stress responses", "metadata": { "title": "Stress Knowledge Map: A knowledge graph resource for systems biology analysis of plant stress responses", "abstract": "Stress Knowledge Map (SKM; https://skm.nib.si) is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical, signaling, and regulatory molecular interactions in plants: a highly curated model of plant stress signaling (PSS; 543 reactions) and a large comprehensive knowledge network (488 390 interactions). Both were constructed by domain experts through systematic curation of diverse literature and database resources. SKM provides a single entry point for investigations of plant stress response and related growth trade-offs, as well as interactive explorations of current knowledge. PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin. Here, we describe the features of SKM and show, through two case studies, how it can be used for complex analyses, including systematic hypothesis generation and design of validation experiments, or to gain new insights into experimental observations in plant biology.", "date": "2024-06-10T00:00:00Z", "citationCount": 8, "authors": [ { "name": "Bleker C." }, { "name": "Ramsak" }, { "name": "Bittner A." }, { "name": "Podpecan V." }, { "name": "Zagorscak M." }, { "name": "Wurzinger B." }, { "name": "Baebler" }, { "name": "Petek M." }, { "name": "Kriznik M." }, { "name": "van Dieren A." }, { "name": "Gruber J." }, { "name": "Afjehi-Sadat L." }, { "name": "Weckwerth W." }, { "name": "Zupanic A." }, { "name": "Teige M." }, { "name": "Vothknecht U.C." }, { "name": "Gruden K." } ], "journal": "Plant Communications" } } ], "credit": [ { "name": "National Institute of Biology, Department of Biotechnology and Systems Biology", "email": null, "url": "http://www.nib.si/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Carissa Bleker", "email": "carissarobyn.bleker@nib.si", "url": null, "orcidid": "https://orcid.org/0000-0003-1617-7145", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Maintainer" ], "note": null }, { "name": "Kristina Gruden", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Živa Ramšak", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Vid Podpečan", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [ "Developer" ], "note": null } ], "owner": "carissa", "additionDate": "2022-05-16T13:26:15.720803Z", "lastUpdate": "2025-06-18T12:10:26.465410Z", "editPermission": { "type": "group", "authors": [ "zagor" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Flye", "description": "Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs.", "homepage": "https://github.com/fenderglass/Flye", "biotoolsID": "Flye", "biotoolsCURIE": "biotools:Flye", "version": [ "2.9.6" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0525", "term": "Genome assembly" }, { "uri": "http://edamontology.org/operation_0524", "term": "De-novo assembly" }, { "uri": "http://edamontology.org/operation_0523", "term": "Mapping assembly" }, { "uri": "http://edamontology.org/operation_3730", "term": "Cross-assembly" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1930", "term": "FASTQ" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1234", "term": "Sequence set (nucleic acid)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3673", "term": "Whole genome sequencing" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" } ], "operatingSystem": [ "Mac", "Linux" ], "language": [ "C++", "Python", "C" ], "license": "BSD-3-Clause", "collectionID": [ "ONTeater" ], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/fenderglass/Flye/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "https://github.com/mikolmogorov/Flye", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1099/mgen.0.000294", "pmid": "31483244", "pmcid": "PMC6807382", "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "Comparison of long-read sequencing technologies in the hybrid assembly of complex bacterial genomes", "abstract": "Illumina sequencing allows rapid, cheap and accurate whole genome bacterial analyses, but short reads (<300 bp) do not usually enable complete genome assembly. Long-read sequencing greatly assists with resolving complex bacterial genomes, particularly when combined with short-read Illumina data (hybrid assembly). However, it is not clear how different long-read sequencing methods affect hybrid assembly accuracy. Relative automation of the assembly process is also crucial to facilitating high-throughput complete bacterial genome reconstruction, avoiding multiple bespoke filtering and data manipulation steps. In this study, we compared hybrid assemblies for 20 bacterial isolates, including two reference strains, using Illumina sequencing and long reads from either Oxford Nanopore Technologies (ONT) or SMRT Pacific Biosciences (PacBio) sequencing platforms. We chose isolates from the family Enterobacteriaceae, as these frequently have highly plastic, repetitive genetic structures, and complete genome reconstruction for these species is relevant for a precise understanding of the epidemiology of antimicrobial resistance. We de novo assembled genomes using the hybrid assembler Unicycler and compared different read processing strategies, as well as comparing to long-read-only assembly with Flye followed by short-read polishing with Pilon. Hybrid assembly with either PacBio or ONT reads facilitated high-quality genome reconstruction, and was superior to the longread assembly and polishing approach evaluated with respect to accuracy and completeness. Combining ONT and Illumina reads fully resolved most genomes without additional manual steps, and at a lower consumables cost per isolate in our setting. Automated hybrid assembly is a powerful tool for complete and accurate bacterial genome assembly.", "date": "2019-01-01T00:00:00Z", "citationCount": 166, "authors": [ { "name": "De Maio N." }, { "name": "Shaw L.P." }, { "name": "Hubbard A." }, { "name": "George S." }, { "name": "Sanderson N.D." }, { "name": "Swann J." }, { "name": "Wick R." }, { "name": "Oun M.A." }, { "name": "Stubberfield E." }, { "name": "Hoosdally S.J." }, { "name": "Crook D.W." }, { "name": "Peto T.E.A." }, { "name": "Sheppard A.E." }, { "name": "Bailey M.J." }, { "name": "Read D.S." }, { "name": "Anjum M.F." }, { "name": "Sarah Walker A." }, { "name": "Stoesser N." } ], "journal": "Microbial Genomics" } }, { "doi": "10.1038/s41587-019-0072-8", "pmid": "30936562", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Assembly of long, error-prone reads using repeat graphs", "abstract": "Accurate genome assembly is hampered by repetitive regions. Although long single molecule sequencing reads are better able to resolve genomic repeats than short-read data, most long-read assembly algorithms do not provide the repeat characterization necessary for producing optimal assemblies. Here, we present Flye, a long-read assembly algorithm that generates arbitrary paths in an unknown repeat graph, called disjointigs, and constructs an accurate repeat graph from these error-riddled disjointigs. We benchmark Flye against five state-of-the-art assemblers and show that it generates better or comparable assemblies, while being an order of magnitude faster. Flye nearly doubled the contiguity of the human genome assembly (as measured by the NGA50 assembly quality metric) compared with existing assemblers.", "date": "2019-05-01T00:00:00Z", "citationCount": 3077, "authors": [ { "name": "Kolmogorov M." }, { "name": "Yuan J." }, { "name": "Lin Y." }, { "name": "Pevzner P.A." } ], "journal": "Nature Biotechnology" } }, { "doi": "10.1038/s41592-020-00971-x", "pmid": "33020656", "pmcid": "PMC10699202", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "metaFlye: scalable long-read metagenome assembly using repeat graphs", "abstract": "Long-read sequencing technologies have substantially improved the assemblies of many isolate bacterial genomes as compared to fragmented short-read assemblies. However, assembling complex metagenomic datasets remains difficult even for state-of-the-art long-read assemblers. Here we present metaFlye, which addresses important long-read metagenomic assembly challenges, such as uneven bacterial composition and intra-species heterogeneity. First, we benchmarked metaFlye using simulated and mock bacterial communities and show that it consistently produces assemblies with better completeness and contiguity than state-of-the-art long-read assemblers. Second, we performed long-read sequencing of the sheep microbiome and applied metaFlye to reconstruct 63 complete or nearly complete bacterial genomes within single contigs. Finally, we show that long-read assembly of human microbiomes enables the discovery of full-length biosynthetic gene clusters that encode biomedically important natural products.", "date": "2020-11-01T00:00:00Z", "citationCount": 511, "authors": [ { "name": "Kolmogorov M." }, { "name": "Bickhart D.M." }, { "name": "Behsaz B." }, { "name": "Gurevich A." }, { "name": "Rayko M." }, { "name": "Shin S.B." }, { "name": "Kuhn K." }, { "name": "Yuan J." }, { "name": "Polevikov E." }, { "name": "Smith T.P.L." }, { "name": "Pevzner P.A." } ], "journal": "Nature Methods" } } ], "credit": [ { "name": "Mikhail Kolmogorov", "email": "fenderglass@gmail.com", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer", "Support" ], "note": null }, { "name": "Yu Lin", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Jeffrey Yuan", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "Pub2Tools", "additionDate": "2019-11-14T20:08:20Z", "lastUpdate": "2025-06-18T10:20:03.775603Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PyRx", "description": "Virtual Screening software for Computational Drug Discovery that can be used to screen libraries of compounds against potential drug targets.", "homepage": "http://pyrx.sourceforge.net/", "biotoolsID": "pyrx", "biotoolsCURIE": "biotools:pyrx", "version": [ "0.9.2" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3431", "term": "Submission" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2430", "term": "Design" } ], "input": [], "output": [], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_2945", "term": "Analysis" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_3336", "term": "Drug discovery" }, { "uri": "http://edamontology.org/topic_2275", "term": "Molecular modelling" }, { "uri": "http://edamontology.org/topic_0154", "term": "Drug targets" }, { "uri": "http://edamontology.org/topic_0154", "term": "Targets" }, { "uri": "http://edamontology.org/topic_0209", "term": "Drug design" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "http://www.mybiosoftware.com/pyrx-0-8-virtual-screening-software-computer-aided-drug-design.html", "type": [ "Software catalogue" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": null, "pmid": "29167582", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Pyridoxine dipharmacophore derivatives as potent glucokinase activators for the treatment of type 2 diabetes mellitus", "abstract": "© 2017 The Author(s).Glucokinase is one of the promising targets for glucose-lowering agents, and the development of GK activators are now considered as one of the most promising strategies for the treatment of type 2 diabetes mellitus. In this work, a series of novel symmetric molecular constructs, in which two pyridoxine moieties are connected via sulfur-containing linkers, have been synthesized and tested in vitro for glucokinase activation potential. The enzyme activation rates by two most active compounds at 100 μM (~150% and 130%) were comparable to that of the reference agent PF-04937319 (~154%). Both leading compounds demonstrated low cytotoxicity and excellent safety profile in acute toxicity experiment in rats after oral administration with LD50 exceeding 2000 mg/kg of body weight. Binding mode of the active compounds in comparison with the reference agent was studied using molecular docking. The leading compounds represent viable preclinical candidates for the treatment of type 2 diabetes mellitus, as well as a promising starting point for the design of structural analogs with improved activity.", "date": "2017-12-01T00:00:00Z", "citationCount": 7, "authors": [ { "name": "Dzyurkevich M.S." }, { "name": "Babkov D.A." }, { "name": "Shtyrlin N.V." }, { "name": "Mayka O.Y." }, { "name": "Iksanova A.G." }, { "name": "Vassiliev P.M." }, { "name": "Balakin K.V." }, { "name": "Spasov A.A." }, { "name": "Tarasov V.V." }, { "name": "Barreto G." }, { "name": "Shtyrlin Y.G." }, { "name": "Aliev G." } ], "journal": "Scientific Reports" } } ], "credit": [ { "name": null, "email": null, "url": "http://mgl.scripps.edu/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Alfiya Iksanova", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-0474-6638", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "Bioinfo", "additionDate": "2017-12-18T00:11:28Z", "lastUpdate": "2025-06-17T16:32:33.365776Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Pavian", "description": "Web application for exploring metagenomics classification results, with a special focus on infectious disease diagnosis. Pinpointing pathogens in metagenomics classification results is often complicated by host and laboratory contaminants as well as many non-pathogenic microbiota. Researchers can analyze, display and transform results from the Kraken and Centrifuge classifiers using interactive tables, heatmaps and flow diagrams.", "homepage": "https://ccb.jhu.edu/software/pavian/", "biotoolsID": "pavian", "biotoolsCURIE": "biotools:pavian", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0226", "term": "Annotation" }, { "uri": "http://edamontology.org/operation_3460", "term": "Taxonomic classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [ "Animal and Crop Genomics", "Biodiversity", "microbiome" ], "maturity": null, "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/fbreitwieser/pavian/tree/master", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "https://ccb.jhu.edu/software/pavian/index.shtml?t=manual", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1101/084715", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [ { "name": null, "email": "fbreitw1@jhmi.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "admin", "additionDate": "2017-08-20T16:34:27Z", "lastUpdate": "2025-06-17T15:12:54.095225Z", "editPermission": { "type": "public", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "xcms", "description": "Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. The packages enables imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files and preprocesses data for high-throughput, untargeted analyte profiling.", "homepage": "http://bioconductor.org/packages/release/bioc/html/xcms.html", "biotoolsID": "xcms", "biotoolsCURIE": "biotools:xcms", "version": [ "3.0.2" ], "otherID": [], "relation": [ { "biotoolsID": "ramclustr", "type": "usedBy" }, { "biotoolsID": "camera", "type": "usedBy" }, { "biotoolsID": "workflow4metabolomics", "type": "usedBy" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3694", "term": "Mass spectrum visualisation" }, { "uri": "http://edamontology.org/operation_3634", "term": "Label-free quantification" }, { "uri": "http://edamontology.org/operation_2428", "term": "Validation" }, { "uri": "http://edamontology.org/operation_3628", "term": "Chromatographic alignment" }, { "uri": "http://edamontology.org/operation_3215", "term": "Peak detection" }, { "uri": "http://edamontology.org/operation_3203", "term": "Chromatogram visualisation" }, { "uri": "http://edamontology.org/operation_3695", "term": "Data filtering" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3650", "term": "NetCDF" }, { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" } ] }, { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrometry spectra" }, "format": [ { "uri": "http://edamontology.org/format_3650", "term": "NetCDF" }, { "uri": "http://edamontology.org/format_3244", "term": "mzML" }, { "uri": "http://edamontology.org/format_3654", "term": "mzXML" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3650", "term": "NetCDF" }, { "uri": "http://edamontology.org/format_3248", "term": "mzQuantML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3383", "term": "Biological imaging" }, { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "R" ], "license": "GPL-2.0", "collectionID": [ "BioConductor", "Bioconda", "Galaxy Tools" ], "maturity": "Mature", "cost": null, "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Germany", "France", "Czech Republic" ], "elixirCommunity": [ "Metabolomics" ], "link": [ { "url": "http://metlin.scripps.edu/download/", "type": [ "Mirror" ], "note": null }, { "url": "https://github.com/sneumann/xcms", "type": [ "Repository" ], "note": "Link to the repository hosting the R code." }, { "url": "https://usegalaxy.eu/root?tool_id=toolshed.g2.bx.psu.edu/repos/lecorguille/xcms_xcmsset/abims_xcms_xcmsSet/3.12.0+galaxy1", "type": [ "Galaxy service" ], "note": null } ], "download": [ { "url": "http://bioconductor/packages/release/bioc/src/contrib/xcms_1.50.1.tar.gz", "type": "Source code", "note": null, "version": null }, { "url": "https://github.com/sneumann/xcms", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "http://bioconductor.org/packages/release/bioc/html/xcms.html", "type": [ "User manual" ], "note": null }, { "url": "https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/lcms-preprocessing/tutorial.html", "type": [ "Training material" ], "note": "Galaxy training material for LC-MS data preprocessing with XCMS" }, { "url": "https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/gc_ms_with_xcms/tutorial.html", "type": [ "Training material" ], "note": "Galaxy training for GC-MS data preprocessing with XCMS" }, { "url": "https://jorainer.github.io/xcmsTutorials/", "type": [ "Training material" ], "note": "Tutorial on using the XCMS R library" } ], "publication": [ { "doi": "10.1093/bioinformatics/btq441", "pmid": "20671148", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Correction of mass calibration gaps in liquid chromatography-mass spectrometry metabolomics data", "abstract": "Motivation: High mass accuracy is an important goal in liquid chromatography-mass spectrometry experiments. Some manufacturers employ a mass calibration system that regularly switches between the analyte and a standard reference compound, and leads to gaps in the analyte data. We present a method for correction of such gaps in global molecular profiling applications such as metabolomics. We demonstrate that it improves peak detection and quantification, successfully recovering the expected number of peaks and intensity distribution in an example metabolomics dataset. © The Author 2010. Published by Oxford University Press. All rights reserved.", "date": "2010-07-29T00:00:00Z", "citationCount": 159, "authors": [ { "name": "Benton H.P." }, { "name": "Want E.J." }, { "name": "Ebbels T.M.D." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Steffen Neumann", "email": "sneumann@ipb-halle.de", "url": null, "orcidid": "https://orcid.org/0000-0002-7899-7192", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "bioconductor_import", "additionDate": "2017-01-17T15:04:54Z", "lastUpdate": "2025-06-17T13:07:05.749022Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-EE", "n.m.palmblad@lumc.nl", "recetox-specdatri", "sneumann" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "mzspeclib", "description": "A python reference implementation of the mzSpecLib spectral library format.", "homepage": "https://github.com/HUPO-PSI/mzspeclib-py", "biotoolsID": "mzspeclib", "biotoolsCURIE": "biotools:mzspeclib", "version": [ "1.0.5" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3434", "term": "Conversion" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_4039", "term": "MSP" }, { "uri": "http://edamontology.org/format_3651", "term": "MGF" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [] } ], "note": null, "cmd": "mzspeclib convert" }, { "operation": [ { "uri": "http://edamontology.org/operation_0336", "term": "Format validation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" } ], "operatingSystem": [], "language": [ "Python" ], "license": "APSL-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Interoperability" ], "elixirNode": [], "elixirCommunity": [ "Proteomics", "Metabolomics" ], "link": [ { "url": "https://www.psidev.info/", "type": [ "Discussion forum" ], "note": null }, { "url": "https://github.com/HUPO-PSI/mzspeclib-py", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/HUPO-PSI/mzspeclib-py", "type": "Source code", "note": null, "version": null }, { "url": "https://pypi.org/project/mzspeclib/", "type": "Software package", "note": null, "version": null } ], "documentation": [ { "url": "https://hupo-psi.github.io/mzSpecLib/", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.analchem.4c04091", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The Proteomics Standards Initiative Standardized Formats for Spectral Libraries and Fragment Ion Peak Annotations: mzSpecLib and mzPAF", "abstract": "Mass spectral libraries are collections of reference spectra, usually associated with specific analytes from which the spectra were generated, that are used for further downstream analysis of new spectra. There are many different formats used for encoding spectral libraries, but none have undergone a standardization process to ensure broad applicability to many applications. As part of the Human Proteome Organization Proteomics Standards Initiative (PSI), we have developed a standardized format for encoding spectral libraries, called mzSpecLib (https://psidev.info/mzSpecLib). It is primarily a data model that flexibly encodes metadata about the library entries using the extensible PSI-MS controlled vocabulary and can be encoded in and converted between different serialization formats. We have also developed a standardized data model and serialization for fragment ion peak annotations, called mzPAF (https://psidev.info/mzPAF). It is defined as a separate standard, since it may be used for other applications besides spectral libraries. The mzSpecLib and mzPAF standards are compatible with existing PSI standards such as ProForma 2.0 and the Universal Spectrum Identifier. The mzSpecLib and mzPAF standards have been primarily defined for peptides in proteomics applications with basic small molecule support. They could be extended in the future to other fields that need to encode spectral libraries for nonpeptidic analytes.", "date": "2024-11-19T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Klein J." }, { "name": "Lam H." }, { "name": "Mak T.D." }, { "name": "Bittremieux W." }, { "name": "Perez-Riverol Y." }, { "name": "Gabriels R." }, { "name": "Shofstahl J." }, { "name": "Hecht H." }, { "name": "Binz P.-A." }, { "name": "Kawano S." }, { "name": "Van Den Bossche T." }, { "name": "Carver J." }, { "name": "Neely B.A." }, { "name": "Mendoza L." }, { "name": "Suomi T." }, { "name": "Claeys T." }, { "name": "Payne T." }, { "name": "Schulte D." }, { "name": "Sun Z." }, { "name": "Hoffmann N." }, { "name": "Zhu Y." }, { "name": "Neumann S." }, { "name": "Jones A.R." }, { "name": "Bandeira N." }, { "name": "Vizcaino J.A." }, { "name": "Deutsch E.W." } ], "journal": "Analytical Chemistry" } } ], "credit": [], "owner": "recetox-specdatri", "additionDate": "2025-06-12T11:47:48.641345Z", "lastUpdate": "2025-06-12T11:57:26.484553Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "wtv", "description": "A CLI/python library that selects characteristic qualitative ions based on \nhttps://github.com/yuanhonglun/WTV_2.0", "homepage": "https://recetox.github.io/wtv/", "biotoolsID": "wtv", "biotoolsCURIE": "biotools:wtv", "version": [ "0.0.2" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3936", "term": "Feature selection" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_4039", "term": "MSP" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_4039", "term": "MSP" } ] } ], "note": null, "cmd": "wtv-cli --msp_path input.msp --outpath output --mz_min 35 --mz_max 400 ..." } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3172", "term": "Metabolomics" } ], "operatingSystem": [], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": "Emerging", "cost": null, "accessibility": null, "elixirPlatform": [ "Tools" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [ "Metabolomics" ], "link": [ { "url": "https://github.com/RECETOX/wtv", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://github.com/RECETOX/wtv", "type": "Source code", "note": null, "version": null }, { "url": "https://pypi.org/project/wtv/", "type": "Software package", "note": null, "version": null }, { "url": "https://github.com/RECETOX/galaxytools/tree/master/tools/wtv", "type": "Tool wrapper (Galaxy)", "note": null, "version": null } ], "documentation": [ { "url": "https://recetox.github.io/wtv/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1016/j.molp.2024.04.012", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "WTV2.0: A high-coverage plant volatilomics method with a comprehensive selective ion monitoring acquisition mode", "abstract": "Volatilomics is essential for understanding the biological functions and fragrance contributions of plant volatiles. However, the annotation coverage achieved using current untargeted and widely targeted volatomics (WTV) methods has been limited by low sensitivity and/or low acquisition coverage. Here, we introduce WTV 2.0, which enabled the construction of a high-coverage library containing 2111 plant volatiles, and report the development of a comprehensive selective ion monitoring (cSIM) acquisition method, including the selection of characteristic qualitative ions with the minimal ion number for each compound and an optimized segmentation method, that can acquire the smallest but sufficient number of ions for most plant volatiles, as well as the automatic qualitative and semi-quantitative analysis of cSIM data. Importantly, the library and acquisition method we developed can be self-expanded by incorporating compounds not present in the library, utilizing the obtained cSIM data. We showed that WTV 2.0 increases the median signal-to-noise ratio by 7.6-fold compared with the untargeted method, doubled the annotation coverage compared with the untargeted and WTV 1.0 methods in tomato fruit, and led to the discovery of menthofuran as a novel flavor compound in passion fruit. WTV 2.0 is a Python library with a user-friendly interface and is applicable to profiling of volatiles and primary metabolites in any species.", "date": "2024-06-03T00:00:00Z", "citationCount": 12, "authors": [ { "name": "Yuan H." }, { "name": "Jiangfang Y." }, { "name": "Liu Z." }, { "name": "Su R." }, { "name": "Li Q." }, { "name": "Fang C." }, { "name": "Huang S." }, { "name": "Liu X." }, { "name": "Fernie A.R." }, { "name": "Luo J." } ], "journal": "Molecular Plant" } } ], "credit": [], "owner": "acquayefrank", "additionDate": "2025-06-02T12:24:30.535794Z", "lastUpdate": "2025-06-12T09:26:29.793603Z", "editPermission": { "type": "group", "authors": [ "recetox-specdatri" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Bracken", "description": "Bracken is a companion program to Kraken 1, KrakenUniq, or Kraken 2 While Kraken classifies reads to multiple levels in the taxonomic tree, Bracken allows estimation of abundance at a single level using those classifications (e.g. Bracken can estimate abundance of species within a sample).", "homepage": "https://ccb.jhu.edu/software/bracken/", "biotoolsID": "bracken", "biotoolsCURIE": "biotools:bracken", "version": [], "otherID": [], "relation": [ { "biotoolsID": "kraken2", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2238", "term": "Statistical calculation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3174", "term": "Metagenomics" }, { "uri": "http://edamontology.org/topic_3697", "term": "Microbial ecology" } ], "operatingSystem": [ "Linux" ], "language": [ "Perl", "Python" ], "license": "GPL-3.0", "collectionID": [ "Animal and Crop Genomics" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/jenniferlu717/Bracken", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/jenniferlu717/Bracken/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [], "documentation": [ { "url": "https://ccb.jhu.edu/software/bracken/index.shtml?t=manual", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.7717/peerj-cs.104", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Bracken: Estimating species abundance in metagenomics data", "abstract": "Metagenomic experiments attempt to characterize microbial communities using high-throughput DNA sequencing. Identification of the microorganisms in a sample provides information about the genetic profile, population structure, and role of microorganisms within an environment. Until recently, most metagenomics studies focused on high-level characterization at the level of phyla, or alternatively sequenced the 16S ribosomalRNAgene that is present in bacterial species. As the cost of sequencing has fallen, though, metagenomics experiments have increasingly used unbiased shotgun sequencing to capture all the organisms in a sample. This approach requires a method for estimating abundance directly from the raw read data. Here we describe a fast, accurate new method that computes the abundance at the species level using the reads collected in a metagenomics experiment. Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN) uses the taxonomic assignments made by Kraken, a very fast read-level classifier, along with information about the genomes themselves to estimate abundance at the species level, the genus level, or above. We demonstrate that Bracken can produce accurate species- and genus-level abundance estimates even when a sample contains multiple near-identical species.", "date": "2017-01-01T00:00:00Z", "citationCount": 1084, "authors": [ { "name": "Lu J." }, { "name": "Breitwieser F.P." }, { "name": "Thielen P." }, { "name": "Salzberg S.L." } ], "journal": "PeerJ Computer Science" } } ], "credit": [ { "name": null, "email": "jlu26@jhmi.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "admin", "additionDate": "2017-08-20T15:17:20Z", "lastUpdate": "2025-06-11T12:25:29.118910Z", "editPermission": { "type": "group", "authors": [ "animalandcropgenomics", "ELIXIR-CZ", "bebatut", "vashokan" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "flumut", "description": "FluMut is an open-source tool designed to search for molecular markers with potential impact on the biological characteristics of Influenza A viruses of the A(H5N1) subtype, starting from complete or partial nucleotide genome sequences.", "homepage": "https://izsvenezie-virology.github.io/FluMut/", "biotoolsID": "flumut", "biotoolsCURIE": "biotools:flumut", "version": [ "0.6.4" ], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [], "operatingSystem": [], "language": [], "license": "gSOAP-1.3b", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/izsvenezie-virology/FluMut", "type": [ "Repository" ], "note": null }, { "url": "https://izsvenezie-virology.github.io/FluMut/", "type": [ "Repository" ], "note": "Website of the tool." }, { "url": "https://doi.org/10.1093/ve/veaf011", "type": [ "Other" ], "note": "Publication link." } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/ve/veaf011", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "FluMut: A tool for mutation surveillance in highly pathogenic H5N1 genomes", "abstract": "Over the past century, Influenza A virus (IAV) has caused four of the five reported pandemics, all of which originated from viruses possessing genome segments of avian origin. The recent spread of highly pathogenic avian influenza (HPAI) viruses, particularly the clade 2.3.4.4b A(H5N1) subtype, has led to an alarming increase in mammalian infections, raising concerns about the potential for future pandemics. In response to this, we developed FluMut, an open-source, cross-platform tool designed to identify molecular markers with potential impacts on H5N1 virus phenotypes. FluMut leverages an up-To-date database, FluMutDB, to rapidly analyze thousands of nucleotide sequences, identifying mutations associated with host adaptation, increased virulence, and antiviral resistance. The tool is available both as a command-line interface and a user-friendly graphical interface, making it accessible to researchers with varying levels of computational expertise. FluMut provides comprehensive outputs, including tables of detected markers, their biological effects, and corresponding literature references. This tool fills a critical gap in the genomic surveillance of HPAI H5N1, facilitating real-Time monitoring of viral evolution and aiding in the identification of mutations that may signal increased pandemic potential. Future updates will extend FluMut's capabilities to other influenza subtypes.", "date": "2025-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Giussani E." }, { "name": "Sartori A." }, { "name": "Salomoni A." }, { "name": "Cavicchio L." }, { "name": "De Battisti C." }, { "name": "Pastori A." }, { "name": "Varotto M." }, { "name": "Zecchin B." }, { "name": "Hughes J." }, { "name": "Monne I." }, { "name": "Fusaro A." } ], "journal": "Virus Evolution" } } ], "credit": [], "owner": "evezeyl", "additionDate": "2025-06-06T11:29:48.238556Z", "lastUpdate": "2025-06-06T12:05:28.550810Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MALDIquant", "description": "MALDIquant is a complete analysis pipeline for matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass spectrometry data. In addition to commonly used plotting and processing methods it includes distinctive features, namely baseline subtraction methods such as morphological filters (TopHat) or the statistics-sensitive non-linear iterative peak-clipping algorithm (SNIP), peak alignment using warping functions, handling of replicated measurements as well as allowing spectra with different resolutions.", "homepage": "https://cran.r-project.org/package=MALDIquant", "biotoolsID": "maldi_quant", "biotoolsCURIE": "biotools:maldi_quant", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" }, { "uri": "http://edamontology.org/operation_3860", "term": "Spectrum calculation" }, { "uri": "http://edamontology.org/operation_3215", "term": "Peak detection" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2884", "term": "Plot" }, "format": [ { "uri": "http://edamontology.org/format_3603", "term": "PNG" } ] } ], "note": null, "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3627", "term": "Mass spectra calibration" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3682", "term": "imzML metadata file" } ] }, { "data": { "uri": "http://edamontology.org/data_2536", "term": "Mass spectrometry data" }, "format": [ { "uri": "http://edamontology.org/format_3839", "term": "ibd" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library", "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [], "language": [ "R" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/sgibb/MALDIquant/", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/sgibb/MALDIquant/issues", "type": [ "Issue tracker" ], "note": null }, { "url": "http://strimmerlab.org/software/maldiquant/", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [ { "url": "https://cran.r-project.org/web/packages/MALDIquant/MALDIquant.pdf", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/bts447", "pmid": "22796955", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Maldiquant: A versatile R package for the analysis of mass spectrometry data", "abstract": "MALDIquant is an R package providing a complete and modular analysis pipeline for quantitative analysis of mass spectrometry data. MALDIquant is specifically designed with application in clinical diagnostics in mind and implements sophisticated routines for importing raw data, preprocessing, non-linear peak alignment and calibration. It also handles technical replicates as well as spectra with unequal resolution. © The Author 2012. Published by Oxford University Press. All rights reserved.", "date": "2012-09-01T00:00:00Z", "citationCount": 499, "authors": [ { "name": "Gibb S." }, { "name": "Strimmer K." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Sebastian Gibb", "email": "mail@sebastiangibb.de", "url": null, "orcidid": "https://orcid.org/0000-0001-7406-4443", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "Korbinian Strimmer", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-7917-2056", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "Kigaard", "additionDate": "2021-05-26T20:42:18Z", "lastUpdate": "2025-06-05T11:28:57.497366Z", "editPermission": { "type": "group", "authors": [ "sizhengZhao" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Radiomic features extraction (EUCAIM-SW-054_T-02-01-003)", "description": "Implemented by GIBI230, this tool is a Docker-based software designed for extracting radiomic features from 3D medical images in NIfTI format using the PyRadiomics library (if DICOM images, the DICOM to NIFTI converter must be run before using this tool). It streamlines the radiomics calculation process by generating a structured CSV file containing all extracted variables from medical images.\nThe dockerized software enables users to configure parameters like filters, bin width, resampling spacing, and normalization settings can be specified. The output radiomic variables provide quantitative information for further analysis in medical imaging research and machine learning applications. \nSpecially important the parameter selection of the band width. For robust and reproducible results, a bin width of 5 is commonly recommended, but it should be adjusted based on image resolution, modality, and noise levels.", "homepage": "https://www.acim.lafe.san.gva.es/acim/?page_id=675&lang=es", "biotoolsID": "gibi230_radiomic_features_extraction", "biotoolsCURIE": "biotools:gibi230_radiomic_features_extraction", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [], "toolType": [], "topic": [], "operatingSystem": [], "language": [ "Python" ], "license": null, "collectionID": [ "EUCAIM" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1148/ryai.230208", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Reproducibility Analysis of Radiomic Features on T2-weighted MR Images after Processing and Segmentation Alterations in Neuroblastoma Tumors", "abstract": "Purpose: To evaluate the reproducibility of radiomics features extracted from T2-weighted MR images in patients with neuroblastoma. Materials and Methods: A retrospective study included 419 patients (mean age, 29 months ± 34 [SD]; 220 male, 199 female) with neu-roblastic tumors diagnosed between 2002 and 2023, within the scope of the PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers (ie, PRIMAGE) project, involving 746 T2/T2*-weighted MRI sequences at diagnosis and/or after initial chemotherapy. Images underwent processing steps (denoising, inhomogeneity bias field cor-rection, normalization, and resampling). Tumors were automatically segmented, and 107 shape, first-order, and second-order radiomics features were extracted, considered as the reference standard. Subsequently, the previous image processing settings were modified, and volumetric masks were applied. New radiomics features were extracted and compared with the reference standard. Reproducibility was assessed using the concordance correlation coefficient (CCC); intrasubject repeatability was measured using the coefficient of variation (CoV). Results: When normalization was omitted, only 5% of the radiomics features demonstrated high reproducibility. Statistical analysis revealed significant changes in the normalization and resampling processes (P < .001). Inhomogeneities removal had the least impact on radiomics (83% of parameters remained stable). Shape features remained stable after mask modifications, with a CCC greater than 0.90. Mask modifications were the most favorable changes for achieving high CCC values, with a radiomics features stability of 70%. Only 7% of second-order radiomics features showed an excellent CoV of less than 0.10. Conclusion: Modifications in the T2-weighted MRI preparation process in patients with neuroblastoma resulted in changes in radiomics features, with normalization identified as the most influential factor for reproducibility. Inhomogeneities removal had the least impact on radiomics features.", "date": "2024-07-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Veiga-Canuto D." }, { "name": "Fernandez-Paton M." }, { "name": "Alberich L.C." }, { "name": "Pastor A.J." }, { "name": "Maya A.G." }, { "name": "Sierra J.M.C." }, { "name": "Nebot C.S." }, { "name": "de las Heras B.M." }, { "name": "Potschger U." }, { "name": "Taschner-Mandl S." }, { "name": "Neri E." }, { "name": "Canete A." }, { "name": "Ladenstein R." }, { "name": "Hero B." }, { "name": "Alberich-Bayarri A." }, { "name": "Marti-Bonmati L." } ], "journal": "Radiology: Artificial Intelligence" } } ], "credit": [], "owner": "pedromiguel_martinez_HULAFE", "additionDate": "2024-12-23T12:44:47.964606Z", "lastUpdate": "2025-06-05T11:07:12.219171Z", "editPermission": { "type": "group", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MR-based glioblastoma tumour detection and segmentation (EUCAIM-SW-021_T-01-02-004)", "description": "The tool performs an automatic segmentation of the possible glioblastoma tumours on MRI images and its subregions", "homepage": "https://www.acim.lafe.san.gva.es/acim/?page_id=675&lang=es", "biotoolsID": "mr-based_glioblastoma_tumour_detection_and_segmentation", "biotoolsCURIE": "biotools:mr-based_glioblastoma_tumour_detection_and_segmentation", "version": [ "1.0.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3365", "term": "Data architecture, analysis and design" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [ "EUCAIM" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.linkedin.com/company/grupo-de-investigaci%C3%B3n-biom%C3%A9dica-en-imagen/", "type": [ "Social media" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.3390/cancers14153648", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Comparative Multicentric Evaluation of Inter-Observer Variability in Manual and Automatic Segmentation of Neuroblastic Tumors in Magnetic Resonance Images", "abstract": "Tumor segmentation is one of the key steps in imaging processing. The goals of this study were to assess the inter-observer variability in manual segmentation of neuroblastic tumors and to analyze whether the state-of-the-art deep learning architecture nnU-Net can provide a robust solution to detect and segment tumors on MR images. A retrospective multicenter study of 132 patients with neuroblastic tumors was performed. Dice Similarity Coefficient (DSC) and Area Under the Receiver Operating Characteristic Curve (AUC ROC) were used to compare segmentation sets. Two more metrics were elaborated to understand the direction of the errors: the modified version of False Positive (FPRm) and False Negative (FNR) rates. Two radiologists manually segmented 46 tumors and a comparative study was performed. nnU-Net was trained-tuned with 106 cases divided into five balanced folds to perform cross-validation. The five resulting models were used as an ensemble solution to measure training (n = 106) and validation (n = 26) performance, independently. The time needed by the model to automatically segment 20 cases was compared to the time required for manual segmentation. The median DSC for manual segmentation sets was 0.969 (±0.032 IQR). The median DSC for the automatic tool was 0.965 (±0.018 IQR). The automatic segmentation model achieved a better performance regarding the FPRm. MR images segmentation variability is similar between radiologists and nnU-Net. Time leverage when using the automatic model with posterior visual validation and manual adjustment corresponds to 92.8%.", "date": "2022-08-01T00:00:00Z", "citationCount": 25, "authors": [ { "name": "Veiga-Canuto D." }, { "name": "Cerda-Alberich L." }, { "name": "Sanguesa Nebot C." }, { "name": "Martinez de las Heras B." }, { "name": "Potschger U." }, { "name": "Gabelloni M." }, { "name": "Carot Sierra J.M." }, { "name": "Taschner-Mandl S." }, { "name": "Duster V." }, { "name": "Canete A." }, { "name": "Ladenstein R." }, { "name": "Neri E." }, { "name": "Marti-Bonmati L." } ], "journal": "Cancers" } }, { "doi": "10.3390/cancers15051622", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Independent Validation of a Deep Learning nnU-Net Tool for Neuroblastoma Detection and Segmentation in MR Images", "abstract": "Objectives. To externally validate and assess the accuracy of a previously trained fully automatic nnU-Net CNN algorithm to identify and segment primary neuroblastoma tumors in MR images in a large children cohort. Methods. An international multicenter, multivendor imaging repository of patients with neuroblastic tumors was used to validate the performance of a trained Machine Learning (ML) tool to identify and delineate primary neuroblastoma tumors. The dataset was heterogeneous and completely independent from the one used to train and tune the model, consisting of 300 children with neuroblastic tumors having 535 MR T2-weighted sequences (486 sequences at diagnosis and 49 after finalization of the first phase of chemotherapy). The automatic segmentation algorithm was based on a nnU-Net architecture developed within the PRIMAGE project. For comparison, the segmentation masks were manually edited by an expert radiologist, and the time for the manual editing was recorded. Different overlaps and spatial metrics were calculated to compare both masks. Results. The median Dice Similarity Coefficient (DSC) was high 0.997; 0.944–1.000 (median; Q1–Q3). In 18 MR sequences (6%), the net was not able neither to identify nor segment the tumor. No differences were found regarding the MR magnetic field, type of T2 sequence, or tumor location. No significant differences in the performance of the net were found in patients with an MR performed after chemotherapy. The time for visual inspection of the generated masks was 7.9 ± 7.5 (mean ± Standard Deviation (SD)) seconds. Those cases where manual editing was needed (136 masks) required 124 ± 120 s. Conclusions. The automatic CNN was able to locate and segment the primary tumor on the T2-weighted images in 94% of cases. There was an extremely high agreement between the automatic tool and the manually edited masks. This is the first study to validate an automatic segmentation model for neuroblastic tumor identification and segmentation with body MR images. The semi-automatic approach with minor manual editing of the deep learning segmentation increases the radiologist’s confidence in the solution with a minor workload for the radiologist.", "date": "2023-03-01T00:00:00Z", "citationCount": 11, "authors": [ { "name": "Veiga-Canuto D." }, { "name": "Cerda-Alberich L." }, { "name": "Jimenez-Pastor A." }, { "name": "Carot Sierra J.M." }, { "name": "Gomis-Maya A." }, { "name": "Sanguesa-Nebot C." }, { "name": "Fernandez-Paton M." }, { "name": "Martinez de las Heras B." }, { "name": "Taschner-Mandl S." }, { "name": "Duster V." }, { "name": "Potschger U." }, { "name": "Simon T." }, { "name": "Neri E." }, { "name": "Alberich-Bayarri A." }, { "name": "Canete A." }, { "name": "Hero B." }, { "name": "Ladenstein R." }, { "name": "Marti-Bonmati L." } ], "journal": "Cancers" } } ], "credit": [ { "name": "GIBI230 - HULAFE", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "casopon", "additionDate": "2025-05-29T12:09:16.704255Z", "lastUpdate": "2025-06-05T08:54:02.757932Z", "editPermission": { "type": "group", "authors": [ "pedromiguel_martinez_HULAFE" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null } ] }