Increasing MicroRNA target prediction confidence by the relative R2 method

Hsiuying Wang, Wen Hsiung Li*

*Corresponding author for this work

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

MicroRNAs (miRNAs) are short noncoding RNAs involved in post-transcriptional gene regulation via binding to mRNAs. Studies show that in a multicellular organism microRNAs (miRNAs) downregulate a large number of target mRNAs. However, predicting the target genes of a miRNA is challenging. Microarray expression profiling has been proposed as a complementary method to increase the confidence of miRNA target prediction, but it can become computationally costly or even intractable when many miRNAs and their effects across multiple tissues are to be considered. Here, we propose a statistical method, the relative R2 method, to find high-confidence targets among the set of potential targets predicted by a computational method such as TargetScanS or by microarray analysis, when expression data of both miRNAs and mRNAs are available for multiple tissues. Applying this method to existing data, we obtain many high-confidence targets in mouse.

Original languageEnglish
Pages (from-to)793-798
Number of pages6
JournalJournal of Theoretical Biology
Volume259
Issue number4
DOIs
StatePublished - 21 Aug 2009

Keywords

  • MicroRNA
  • Microarray
  • Regression model
  • TargetScanS

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