Literature DB >> 25053842

miRdentify: high stringency miRNA predictor identifies several novel animal miRNAs.

Thomas B Hansen1, Morten T Venø2, Jørgen Kjems2, Christian K Damgaard3.   

Abstract

During recent years, miRNAs have been shown to play important roles in the regulation of gene expression. Accordingly, much effort has been put into the discovery of novel uncharacterized miRNAs in various organisms. miRNAs are structurally defined by a hairpin-loop structure recognized by the two-step processing apparatus, Drosha and Dicer, necessary for the production of mature ∼ 22-nucleotide miRNA guide strands. With the emergence of high-throughput sequencing applications, tools have been developed to identify miRNAs and profile their expression based on sequencing reads. However, as the read depth increases, false-positive predictions increase using established algorithms, underscoring the need for more stringent approaches. Here we describe a transparent pipeline for confident miRNA identification in animals, termed miRdentify. We show that miRdentify confidently discloses more than 400 novel miRNAs in humans, including the first male-specific miRNA, which we successfully validate. Moreover, novel miRNAs are predicted in the mouse, the fruit fly and nematodes, suggesting that the pipeline applies to all animals. The entire software package is available at www.ncrnalab.dk/mirdentify.
© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2014        PMID: 25053842      PMCID: PMC4176371          DOI: 10.1093/nar/gku598

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  44 in total

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Journal:  Genome Res       Date:  2010-12-22       Impact factor: 9.043

4.  Mammalian microRNAs: experimental evaluation of novel and previously annotated genes.

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Journal:  Nat Struct Mol Biol       Date:  2009-08-27       Impact factor: 15.369

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5.  Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.

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Review 6.  A Review on Recent Computational Methods for Predicting Noncoding RNAs.

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