Cepred : Predicting the co-expression patterns of the human intronic microRNAs with their host genes

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DOIResolve DOI: http://doi.org/10.1371/journal.pone.0004421
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TypeArticle
Journal titlePLoS ONE
Volume4
Issue2
Pages17; # of pages: 7
SubjectGenes; genome; Human; MicroRNA; pha
AbstractIdentifying the tissues in which a microRNA is expressed could enhance the understanding of the functions, the biological processes, and the diseases associated with that microRNA. However, the mechanisms of microRNA biogenesis and expression remain largely unclear and the identification of the tissues in which a microRNA is expressed is limited. Here, we present a machine learning based approach to predict whether an intronic microRNA show high co-expression with its host gene, by doing so, we could infer the tissues in which a microRNA is high expressed through the expression profile of its host gene. Our approach is able to achieve an accuracy of 79% in the leave-one-out cross validation and 95% on an independent testing dataset. We further estimated our method through comparing the predicted tissue specific microRNAs and the tissue specific microRNAs identified by biological experiments. This study presented a valuable tool to predict the co-expression patterns between human intronic microRNAs and their host genes, which would also help to understand the microRNA expression and regulation mechanisms. Finally, this framework can be easily extended to other species.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada; NRC Biotechnology Research Institute
Peer reviewedNo
NRC number50657
NPARC number12919062
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Record identifier63d17938-38d9-425d-a1f4-0ae8385fa124
Record created2009-11-10
Record modified2016-05-09
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