Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/62082
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Type: Journal article
Title: Identifying functional miRNA-mRNA regulatory module with correspondence latent dirichlet allocation
Author: Liu, B.
Liu, L.
Tsykin, A.
Goodall, G.
Green, J.
Zhu, M.
Kim, C.
Li, J.
Citation: Bioinformatics, 2010; 26(24):3105-3111
Publisher: Oxford Univ Press
Issue Date: 2010
ISSN: 1367-4803
1460-2059
Statement of
Responsibility: 
Bing Liu, Lin Liu, Anna Tsykin, Gregory J. Goodall, Jeffrey E. Green, Min Zhu, Chang Hee Kim and Jiuyong Li
Abstract: MOTIVATION: MicroRNAs (miRNAs) are small non-coding RNAs that cause mRNA degradation and translational inhibition. They are important regulators of development and cellular homeostasis through their control of diverse processes. Recently, great efforts have been made to elucidate their regulatory mechanism, but the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With more and more matched expression profiles of miRNAs and mRNAs having been made available, it is of great interest to utilize both expression profiles to discover the functional regulatory networks of miRNAs and their target mRNAs for potential biological processes that they may participate in. RESULTS: We present a probabilistic graphical model to discover functional miRNA regulatory modules at potential biological levels by integrating heterogeneous datasets, including expression profiles of miRNAs and mRNAs, with or without the prior target binding information. We applied this model to a mouse mammary dataset. It effectively captured several biological process specific modules involving miRNAs and their target mRNAs. Furthermore, without using prior target binding information, the identified miRNAs and mRNAs in each module show a large proportion of overlap with predicted miRNA target relationships, suggesting that expression profiles are crucial for both target identification and discovery of regulatory modules.
Keywords: Animals; Mice; Mammary Neoplasms, Experimental; MicroRNAs; RNA, Messenger; Models, Statistical; Gene Expression Profiling; Gene Expression Regulation; Female; Gene Regulatory Networks
Rights: © The Author 2010.
RMID: 0020101255
DOI: 10.1093/bioinformatics/btq576
Appears in Collections:Molecular and Biomedical Science publications

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