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      Human MicroRNA Targets

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          Abstract

          MicroRNAs (miRNAs) interact with target mRNAs at specific sites to induce cleavage of the message or inhibit translation. The specific function of most mammalian miRNAs is unknown. We have predicted target sites on the 3′ untranslated regions of human gene transcripts for all currently known 218 mammalian miRNAs to facilitate focused experiments. We report about 2,000 human genes with miRNA target sites conserved in mammals and about 250 human genes conserved as targets between mammals and fish. The prediction algorithm optimizes sequence complementarity using position-specific rules and relies on strict requirements of interspecies conservation. Experimental support for the validity of the method comes from known targets and from strong enrichment of predicted targets in mRNAs associated with the fragile X mental retardation protein in mammals. This is consistent with the hypothesis that miRNAs act as sequence-specific adaptors in the interaction of ribonuclear particles with translationally regulated messages. Overrepresented groups of targets include mRNAs coding for transcription factors, components of the miRNA machinery, and other proteins involved in translational regulation, as well as components of the ubiquitin machinery, representing novel feedback loops in gene regulation. Detailed information about target genes, target processes, and open-source software for target prediction (miRanda) is available at http://www.microrna.org. Our analysis suggests that miRNA genes, which are about 1% of all human genes, regulate protein production for 10% or more of all human genes.

          Abstract

          This computational analysis provides evidence that as many as 10% of human genes are targets for regulation by small RNA molecules called microRNAs

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          Most cited references149

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          Basic local alignment search tool.

          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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            MicroRNAs

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              Mfold web server for nucleic acid folding and hybridization prediction.

              M Zuker (2003)
              The abbreviated name, 'mfold web server', describes a number of closely related software applications available on the World Wide Web (WWW) for the prediction of the secondary structure of single stranded nucleic acids. The objective of this web server is to provide easy access to RNA and DNA folding and hybridization software to the scientific community at large. By making use of universally available web GUIs (Graphical User Interfaces), the server circumvents the problem of portability of this software. Detailed output, in the form of structure plots with or without reliability information, single strand frequency plots and 'energy dot plots', are available for the folding of single sequences. A variety of 'bulk' servers give less information, but in a shorter time and for up to hundreds of sequences at once. The portal for the mfold web server is http://www.bioinfo.rpi.edu/applications/mfold. This URL will be referred to as 'MFOLDROOT'.
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                Author and article information

                Journal
                PLoS Biol
                pbio
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                1544-9173
                1545-7885
                November 2004
                5 October 2004
                : 2
                : 11
                : e363
                Affiliations
                [1] 1Computational Biology Center, Memorial Sloan-Kettering Cancer Center New York, New YorkUnited States of America
                [2] 2Wellcome Trust Sanger Institute CambridgeUnited Kingdom
                [3] 3Laboratory of RNA Molecular Biology, The Rockefeller University New York, New YorkUnited States of America
                [4] 4Department of Systems Biology, Harvard Medical School Boston, MassachusettsUnited States of America
                Article
                10.1371/journal.pbio.0020363
                521178
                15502875
                5842bde0-699a-431c-aa11-8038126801c5
                Copyright: © 2004 John et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
                History
                : 18 May 2004
                : 20 August 2004
                Categories
                Research Article
                Bioinformatics/Computational Biology
                Cell Biology
                Genetics/Genomics/Gene Therapy
                Molecular Biology/Structural Biology
                Homo (Human)

                Life sciences
                Life sciences

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