標題: Increasing MicroRNA target prediction confidence by the relative R(2) method
作者: Wang, Hsiuying
Li, Wen-Hsiung
統計學研究所
Institute of Statistics
公開日期: 21-Aug-2009
摘要: 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 pro. ling 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 R(2) 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. (C) 2009 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.jtbi.2009.05.007
http://hdl.handle.net/11536/6792
ISSN: 0022-5193
DOI: 10.1016/j.jtbi.2009.05.007
期刊: JOURNAL OF THEORETICAL BIOLOGY
Volume: 259
Issue: 4
起始頁: 793
結束頁: 798
Appears in Collections:Articles