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      MAGIA 2: from miRNA and genes expression data integrative analysis to microRNA–transcription factor mixed regulatory circuits (2012 update)

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          Abstract

          MAGIA 2 ( http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA 2 performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA 2 tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target.

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          Most cited references40

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          miRecords: an integrated resource for microRNA–target interactions

          MicroRNAs (miRNAs) are an important class of small noncoding RNAs capable of regulating other genes’ expression. Much progress has been made in computational target prediction of miRNAs in recent years. More than 10 miRNA target prediction programs have been established, yet, the prediction of animal miRNA targets remains a challenging task. We have developed miRecords, an integrated resource for animal miRNA–target interactions. The Validated Targets component of this resource hosts a large, high-quality manually curated database of experimentally validated miRNA–target interactions with systematic documentation of experimental support for each interaction. The current release of this database includes 1135 records of validated miRNA–target interactions between 301 miRNAs and 902 target genes in seven animal species. The Predicted Targets component of miRecords stores predicted miRNA targets produced by 11 established miRNA target prediction programs. miRecords is expected to serve as a useful resource not only for experimental miRNA researchers, but also for informatics scientists developing the next-generation miRNA target prediction programs. The miRecords is available at http://miRecords.umn.edu/miRecords.
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            Physiological and pathological roles for microRNAs in the immune system.

            Mammalian microRNAs (miRNAs) have recently been identified as important regulators of gene expression, and they function by repressing specific target genes at the post-transcriptional level. Now, studies of miRNAs are resolving some unsolved issues in immunology. Recent studies have shown that miRNAs have unique expression profiles in cells of the innate and adaptive immune systems and have pivotal roles in the regulation of both cell development and function. Furthermore, when miRNAs are aberrantly expressed they can contribute to pathological conditions involving the immune system, such as cancer and autoimmunity; they have also been shown to be useful as diagnostic and prognostic indicators of disease type and severity. This Review discusses recent advances in our understanding of both the intended functions of miRNAs in managing immune cell biology and their pathological roles when their expression is dysregulated.
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              MicroRNA control of signal transduction.

              MicroRNAs (miRNAs) are integral elements in the post-transcriptional control of gene expression. After the identification of hundreds of miRNAs, the challenge is now to understand their specific biological function. Signalling pathways are ideal candidates for miRNA-mediated regulation owing to the sharp dose-sensitive nature of their effects. Indeed, emerging evidence suggests that miRNAs affect the responsiveness of cells to signalling molecules such as transforming growth factor-beta, WNT, Notch and epidermal growth factor. As such, miRNAs serve as nodes of signalling networks that ensure homeostasis and regulate cancer, metastasis, fibrosis and stem cell biology.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                July 2012
                July 2012
                21 May 2012
                21 May 2012
                : 40
                : Web Server issue
                : W13-W21
                Affiliations
                1Department of Biology, University of Padova, Padova 35131, 2Department of Statistical Science, University of Padova, Padova 35121 and 3Department of Comparative Biomedicine and Food Sciences, University of Padova, Padova 35020, Italy
                Author notes
                *To whom correspondence should be addressed. Tel: +39 049 827 7401; Fax: +39 049 827 6159; Email: chiara.romualdi@ 123456unipd.it
                Correspondence may also be addressed to Stefania Bortoluzzi. Tel: +39 049 827 6502; Fax: +39 049 827 6209; Email: stefania.bortoluzzi@ 123456unipd.it

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

                Article
                gks460
                10.1093/nar/gks460
                3394337
                22618880
                8d648458-da04-4788-81e5-df65054342bd
                © The Author(s) 2012. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 1 March 2012
                : 23 April 2012
                : 30 April 2012
                Page count
                Pages: 9
                Categories
                Articles

                Genetics
                Genetics

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