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      MIENTURNET: an interactive web tool for microRNA-target enrichment and network-based analysis

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          Abstract

          Background

          miRNAs regulate the expression of several genes with one miRNA able to target multiple genes and with one gene able to be simultaneously targeted by more than one miRNA. Therefore, it has become indispensable to shorten the long list of miRNA-target interactions to put in the spotlight in order to gain insight into understanding the regulatory mechanism orchestrated by miRNAs in various cellular processes. A reasonable solution is certainly to prioritize miRNA-target interactions to maximize the effectiveness of the downstream analysis.

          Results

          We propose a new and easy-to-use web tool MIENTURNET (MicroRNA ENrichment TURned NETwork) that receives in input a list of miRNAs or mRNAs and tackles the problem of prioritizing miRNA-target interactions by performing a statistical analysis followed by a fully featured network-based visualization and analysis. The statistics is used to assess the significance of an over-representation of miRNA-target interactions and then MIENTURNET filters based on the statistical significance associated with each miRNA-target interaction. In addition, the holistic approach of the network theory is used to infer possible evidences of miRNA regulation by capturing emergent properties of the miRNA-target regulatory network that would be not evident through a pairwise analysis of the individual components.

          Conclusion

          MIENTURNET offers the possibility to consistently perform both statistical and network-based analyses by using only a single tool leading to a more effective prioritization of the miRNA-target interactions. This has the potential to avoid researchers without computational and informatics skills to navigate multiple websites and thus to independently investigate miRNA activity in every cellular process of interest in an easy and at the same time exhaustive way thanks to the intuitive web interface. The web application along with a well-documented and comprehensive user guide are freely available at http://userver.bio.uniroma1.it/apps/mienturnet/ without any login requirement.

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          Most cited references8

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          Systematic discovery of regulatory motifs in human promoters and 3' UTRs by comparison of several mammals.

          Comprehensive identification of all functional elements encoded in the human genome is a fundamental need in biomedical research. Here, we present a comparative analysis of the human, mouse, rat and dog genomes to create a systematic catalogue of common regulatory motifs in promoters and 3' untranslated regions (3' UTRs). The promoter analysis yields 174 candidate motifs, including most previously known transcription-factor binding sites and 105 new motifs. The 3'-UTR analysis yields 106 motifs likely to be involved in post-transcriptional regulation. Nearly one-half are associated with microRNAs (miRNAs), leading to the discovery of many new miRNA genes and their likely target genes. Our results suggest that previous estimates of the number of human miRNA genes were low, and that miRNAs regulate at least 20% of human genes. The overall results provide a systematic view of gene regulation in the human, which will be refined as additional mammalian genomes become available.
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            A Brief Review on the Mechanisms of miRNA Regulation

            MicroRNAs (miRNAs) are a class of short, endogenously-initiated non-coding RNAs that post-transcriptionally control gene expression via either translational repression or mRNA degradation. It is becoming evident that miRNAs are playing significant roles in regulatory mechanisms operating in various organisms, including developmental timing and host-pathogen interactions as well as cell differentiation, proliferation, apoptosis and tumorigenesis. Likewise, as a regulatory element, miRNA itself is coordinatively modulated by multifarious effectors when carrying out basic functions, such as SNP, miRNA editing, methylation and circadian clock. This mini-review summarized the current understanding of interactions between miRNAs and their targets, including recent advancements in deciphering the regulatory mechanisms that control the biogenesis and functionality of miRNAs in various cellular processes.
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              WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research

              Abstract WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities.
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                Author and article information

                Contributors
                valerio.licursi@uniroma1.it
                federica.conte@iasi.cnr.it
                giulia.fiscon@iasi.cnr.it
                paola.paci@iasi.cnr.it
                Journal
                BMC Bioinformatics
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central (London )
                1471-2105
                4 November 2019
                4 November 2019
                2019
                : 20
                : 545
                Affiliations
                [1 ]ISNI 0000 0001 1940 4177, GRID grid.5326.2, Institute for Systems Analysis and Computer Science “Antonio Ruberti”, National Research Council, ; Via dei Taurini 19, Rome, 00185 Italy
                [2 ]GRID grid.7841.a, Department of Biology and Biotechnology “Charles Darwin”, , “Sapienza” University of Rome, ; Via dei Sardi 70, Rome, 00185 Italy
                Author information
                http://orcid.org/0000-0002-8172-1437
                http://orcid.org/0000-0003-0427-1476
                http://orcid.org/0000-0002-3354-8203
                http://orcid.org/0000-0002-9393-2047
                Article
                3105
                10.1186/s12859-019-3105-x
                6829817
                31684860
                b1480032-c95a-4af6-90eb-0e9c4dd5a9ea
                © The Author(s) 2019

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 26 July 2019
                : 20 September 2019
                Categories
                Software
                Custom metadata
                © The Author(s) 2019

                Bioinformatics & Computational biology
                network analysis,mirna regulatory network,bioinformatics tool

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