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      miRPathDB 2.0: a novel release of the miRNA Pathway Dictionary Database

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          Abstract

          Since the initial release of miRPathDB, tremendous progress has been made in the field of microRNA (miRNA) research. New miRNA reference databases have emerged, a vast amount of new miRNA candidates has been discovered and the number of experimentally validated target genes has increased considerably. Hence, the demand for a major upgrade of miRPathDB, including extended analysis functionality and intuitive visualizations of query results has emerged. Here, we present the novel release 2.0 of the miRNA Pathway Dictionary Database ( miRPathDB) that is freely accessible at https://mpd.bioinf.uni-sb.de/. miRPathDB 2.0 comes with a ten-fold increase of pre-processed data. In total, the updated database provides putative associations between 27 452 (candidate) miRNAs, 28 352 targets and 16 833 pathways for Homo sapiens, as well as interactions of 1978 miRNAs, 24 898 targets and 6511 functional categories for Mus musculus. Additionally, we analyzed publications citing miRPathDB to identify common use-cases and further extensions. Based on this evaluation, we added new functionality for interactive visualizations and down-stream analyses of bulk queries. In summary, the updated version of miRPathDB, with its new custom-tailored features, is one of the most comprehensive and advanced resources for miRNAs and their target pathways.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            miRWalk: An online resource for prediction of microRNA binding sites

            miRWalk is an open-source platform providing an intuitive interface that generates predicted and validated miRNA-binding sites of known genes of human, mouse, rat, dog and cow. The core of miRWalk is the miRNA target site prediction with the random-forest-based approach software TarPmiR searching the complete transcript sequence including the 5’-UTR, CDS and 3’-UTR. Moreover, it integrates results other databases with predicted and validated miRNA-target interactions. The focus is set on a modular design and extensibility as well as a fast update cycle. The database is available using Python, MySQL and HTML/Javascript Database URL: http://mirwalk.umm.uni-heidelberg.de.
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              DIANA-TarBase v8: a decade-long collection of experimentally supported miRNA–gene interactions

              Abstract DIANA-TarBase v8 (http://www.microrna.gr/tarbase) is a reference database devoted to the indexing of experimentally supported microRNA (miRNA) targets. Its eighth version is the first database indexing >1 million entries, corresponding to ∼670 000 unique miRNA-target pairs. The interactions are supported by >33 experimental methodologies, applied to ∼600 cell types/tissues under ∼451 experimental conditions. It integrates information on cell-type specific miRNA–gene regulation, while hundreds of thousands of miRNA-binding locations are reported. TarBase is coming of age, with more than a decade of continuous support in the non-coding RNA field. A new module has been implemented that enables the browsing of interactions through different filtering combinations. It permits easy retrieval of positive and negative miRNA targets per species, methodology, cell type and tissue. An incorporated ranking system is utilized for the display of interactions based on the robustness of their supporting methodologies. Statistics, pie-charts and interactive bar-plots depicting the database content are available through a dedicated result page. An intuitive interface is introduced, providing a user-friendly application with flexible options to different queries.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2020
                06 November 2019
                06 November 2019
                : 48
                : D1
                : D142-D147
                Affiliations
                [1 ] Chair for Bioinformatics , Saarland Informatics Campus, 66123 Saarbrücken, Germany
                [2 ] Chair for Clinical Bioinformatics, Saarland University , 66123 Saarbrücken, Germany
                [3 ] EMD Digital, Merck KGaA , Darmstadt, Germany
                [4 ] Department of Human Genetics, Saarland University , 66421 Homburg, Germany
                [5 ] School of Medicine Office, Stanford University , Stanford, CA, USA
                [6 ] Department of Neurology and Neurological Sciences, Stanford University , Stanford, CA, USA
                Author notes
                To whom correspondence should be addressed: Tel: +49 681 302 68611; Email: andreas.keller@ 123456ccb.uni-saarland.de

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.

                Author information
                http://orcid.org/0000-0002-8223-3750
                http://orcid.org/0000-0001-9330-9290
                http://orcid.org/0000-0003-1967-2918
                http://orcid.org/0000-0002-5361-0895
                Article
                gkz1022
                10.1093/nar/gkz1022
                7145528
                31691816
                29b9c5d7-a2c4-420f-b142-edf82a64885c
                © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 19 October 2019
                : 17 October 2019
                : 15 September 2019
                Page count
                Pages: 6
                Funding
                Funded by: Saarland University 10.13039/501100005690
                Categories
                Database Issue

                Genetics
                Genetics

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