Inferring functional miRNA-mRNA regulatory modules in epithelial-mesenchymal transition with a probabilistic topic model

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• 作者：Junpeng Zhang^a ; ^{zhangjunpeng_508@yahoo.com.cn}  ; [Author Vitae] ; Bing Liu^b ; ^{Bing.Liu@newcastle.edu.au}  ; [Author Vitae] ; Jianfeng He^a ; ^{jfenghe@kmust.edu.cn}  ; [Author Vitae] ; Lei Ma^a ; ^{roy_l_murray@hotmail.com}  ; [Author Vitae] ; Jiuyong Li^c ; ^{jiuyong.li@unisa.edu.au}  ; [Author Vitae]
• 关键词：miRNA ; mRNA ; Functional regulatory modules ; Epithelial&ndash ; mesenchymal transition ; Probabilistic topic model
• 刊名：Computers in Biology and Medicine
• 出版年：2012
• 期刊代码：70_00104825
• 类别：med
• 出版时间：April, 2012
• 卷：42
• 期：4
• 页码：428-437
• 文件大小：1349 K

摘要

MicroRNAs (miRNAs) play important roles in gene regulatory networks. In this paper, we propose a probabilistic topic model to infer regulatory networks of miRNAs and their target mRNAs for specific biological conditions at the post-transcriptional level, so-called functional miRNA-mRNA regulatory modules (FMRMs). The probabilistic model used in this paper can effectively capture the relationship between miRNAs and mRNAs in specific cellular conditions. Furthermore, the proposed method identifies negatively and positively correlated miRNA-mRNA pairs which are associated with epithelial, mesenchymal, and other condition in EMT (epithelial-mesenchymal transition) data set, respectively. Results on EMT data sets show that the inferred FMRMs can potentially construct the biological chain of 鈥樷€?at the post-transcriptional level.