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      Is Open Access

      miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology

      research-article
      , , ,
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          miRNet is an easy-to-use, web-based platform designed to help elucidate microRNA (miRNA) functions by integrating users' data with existing knowledge via network-based visual analytics. Since its first release in 2016, miRNet has been accessed by >20 000 researchers worldwide, with ∼100 users on a daily basis. While version 1.0 was focused primarily on miRNA-target gene interactions, it has become clear that in order to obtain a global view of miRNA functions, it is necessary to bring other important players into the context during analysis. Driven by this concept, in miRNet version 2.0, we have (i) added support for transcription factors (TFs) and single nucleotide polymorphisms (SNPs) that affect miRNAs, miRNA-binding sites or target genes, whilst also greatly increased (>5-fold) the underlying knowledgebases of miRNAs, ncRNAs and disease associations; (ii) implemented new functions to allow creation and visual exploration of multipartite networks, with enhanced support for in situ functional analysis and (iii) revamped the web interface, optimized the workflow, and introduced microservices and web application programming interface (API) to sustain high-performance, real-time data analysis. The underlying R package is also released in tandem with version 2.0 to allow more flexible data analysis for R programmers. The miRNet 2.0 website is freely available at https://www.mirnet.ca.

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          Most cited references40

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          Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites

          mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.
            • Record: found
            • Abstract: found
            • Article: not found

            Roles for microRNAs in conferring robustness to biological processes.

            Biological systems use a variety of mechanisms to maintain their functions in the face of environmental and genetic perturbations. Increasing evidence suggests that, among their roles as posttranscriptional repressors of gene expression, microRNAs (miRNAs) help to confer robustness to biological processes by reinforcing transcriptional programs and attenuating aberrant transcripts, and they may in some network contexts help suppress random fluctuations in transcript copy number. These activities have important consequences for normal development and physiology, disease, and evolution. Here, we will discuss examples and principles of miRNAs that contribute to robustness in animal systems. Copyright © 2012 Elsevier Inc. All rights reserved.
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              miRTarBase 2020: updates to the experimentally validated microRNA–target interaction database

              Abstract MicroRNAs (miRNAs) are small non-coding RNAs (typically consisting of 18–25 nucleotides) that negatively control expression of target genes at the post-transcriptional level. Owing to the biological significance of miRNAs, miRTarBase was developed to provide comprehensive information on experimentally validated miRNA–target interactions (MTIs). To date, the database has accumulated >13,404 validated MTIs from 11,021 articles from manual curations. In this update, a text-mining system was incorporated to enhance the recognition of MTI-related articles by adopting a scoring system. In addition, a variety of biological databases were integrated to provide information on the regulatory network of miRNAs and its expression in blood. Not only targets of miRNAs but also regulators of miRNAs are provided to users for investigating the up- and downstream regulations of miRNAs. Moreover, the number of MTIs with high-throughput experimental evidence increased remarkably (validated by CLIP-seq technology). In conclusion, these improvements promote the miRTarBase as one of the most comprehensively annotated and experimentally validated miRNA–target interaction databases. The updated version of miRTarBase is now available at http://miRTarBase.cuhk.edu.cn/.

                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                02 July 2020
                02 June 2020
                02 June 2020
                : 48
                : W1
                : W244-W251
                Affiliations
                Department of Human Genetics, McGill University , Montreal, Quebec, Canada
                Institute of Parasitology, McGill University , Montreal, Quebec, Canada
                Institute of Parasitology, McGill University , Montreal, Quebec, Canada
                Department of Human Genetics, McGill University , Montreal, Quebec, Canada
                Institute of Parasitology, McGill University , Montreal, Quebec, Canada
                Department of Animal Science, McGill University , Montreal, Quebec, Canada
                Author notes
                To whom correspondence should be addressed. Tel: +1 514 398 8668; Email: jeff.xia@ 123456mcgill.ca
                Author information
                http://orcid.org/0000-0002-0966-7923
                http://orcid.org/0000-0003-2040-2624
                Article
                gkaa467
                10.1093/nar/gkaa467
                7319552
                32484539
                8af5d47a-24c6-4e29-8b40-9eadfa0151d4
                © The Author(s) 2020. 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 License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 May 2020
                : 27 April 2020
                : 05 March 2020
                Page count
                Pages: 8
                Funding
                Funded by: NSERC, DOI 10.13039/501100000038;
                Funded by: Genome Canada, DOI 10.13039/100008762;
                Funded by: Canada Research Chairs, DOI 10.13039/501100001804;
                Categories
                AcademicSubjects/SCI00010
                Web Server Issue

                Genetics
                Genetics

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