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Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses

Biomedical data repositories such as the Gene Expression Omnibus (GEO) enable the search and discovery of relevant biomedical digital data objects. Similarly, resources such as OMICtools, index bioinformatics tools that can extract knowledge from these digital data objects. However, systematic acces...

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Autores principales: Torre, Denis, Krawczuk, Patrycja, Jagodnik, Kathleen M., Lachmann, Alexander, Wang, Zichen, Wang, Lily, Kuleshov, Maxim V., Ma’ayan, Avi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5827688/
https://www.ncbi.nlm.nih.gov/pubmed/29485625
http://dx.doi.org/10.1038/sdata.2018.23
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author Torre, Denis
Krawczuk, Patrycja
Jagodnik, Kathleen M.
Lachmann, Alexander
Wang, Zichen
Wang, Lily
Kuleshov, Maxim V.
Ma’ayan, Avi
author_facet Torre, Denis
Krawczuk, Patrycja
Jagodnik, Kathleen M.
Lachmann, Alexander
Wang, Zichen
Wang, Lily
Kuleshov, Maxim V.
Ma’ayan, Avi
author_sort Torre, Denis
collection PubMed
description Biomedical data repositories such as the Gene Expression Omnibus (GEO) enable the search and discovery of relevant biomedical digital data objects. Similarly, resources such as OMICtools, index bioinformatics tools that can extract knowledge from these digital data objects. However, systematic access to pre-generated ‘canned’ analyses applied by bioinformatics tools to biomedical digital data objects is currently not available. Datasets2Tools is a repository indexing 31,473 canned bioinformatics analyses applied to 6,431 datasets. The Datasets2Tools repository also contains the indexing of 4,901 published bioinformatics software tools, and all the analyzed datasets. Datasets2Tools enables users to rapidly find datasets, tools, and canned analyses through an intuitive web interface, a Google Chrome extension, and an API. Furthermore, Datasets2Tools provides a platform for contributing canned analyses, datasets, and tools, as well as evaluating these digital objects according to their compliance with the findable, accessible, interoperable, and reusable (FAIR) principles. By incorporating community engagement, Datasets2Tools promotes sharing of digital resources to stimulate the extraction of knowledge from biomedical research data. Datasets2Tools is freely available from: http://amp.pharm.mssm.edu/datasets2tools.
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spelling pubmed-58276882018-03-19 Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses Torre, Denis Krawczuk, Patrycja Jagodnik, Kathleen M. Lachmann, Alexander Wang, Zichen Wang, Lily Kuleshov, Maxim V. Ma’ayan, Avi Sci Data Article Biomedical data repositories such as the Gene Expression Omnibus (GEO) enable the search and discovery of relevant biomedical digital data objects. Similarly, resources such as OMICtools, index bioinformatics tools that can extract knowledge from these digital data objects. However, systematic access to pre-generated ‘canned’ analyses applied by bioinformatics tools to biomedical digital data objects is currently not available. Datasets2Tools is a repository indexing 31,473 canned bioinformatics analyses applied to 6,431 datasets. The Datasets2Tools repository also contains the indexing of 4,901 published bioinformatics software tools, and all the analyzed datasets. Datasets2Tools enables users to rapidly find datasets, tools, and canned analyses through an intuitive web interface, a Google Chrome extension, and an API. Furthermore, Datasets2Tools provides a platform for contributing canned analyses, datasets, and tools, as well as evaluating these digital objects according to their compliance with the findable, accessible, interoperable, and reusable (FAIR) principles. By incorporating community engagement, Datasets2Tools promotes sharing of digital resources to stimulate the extraction of knowledge from biomedical research data. Datasets2Tools is freely available from: http://amp.pharm.mssm.edu/datasets2tools. Nature Publishing Group 2018-02-27 /pmc/articles/PMC5827688/ /pubmed/29485625 http://dx.doi.org/10.1038/sdata.2018.23 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Torre, Denis
Krawczuk, Patrycja
Jagodnik, Kathleen M.
Lachmann, Alexander
Wang, Zichen
Wang, Lily
Kuleshov, Maxim V.
Ma’ayan, Avi
Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses
title Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses
title_full Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses
title_fullStr Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses
title_full_unstemmed Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses
title_short Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses
title_sort datasets2tools, repository and search engine for bioinformatics datasets, tools and canned analyses
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5827688/
https://www.ncbi.nlm.nih.gov/pubmed/29485625
http://dx.doi.org/10.1038/sdata.2018.23
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