Kunming University of Science and Technology, Kunming, China.
Comput Biol Med. 2012 Apr;42(4):428-37. doi: 10.1016/j.compbiomed.2011.12.011. Epub 2012 Jan 15.
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 'miRNA→mRNA→condition' at the post-transcriptional level.
微小 RNA（miRNA）在基因调控网络中发挥着重要作用。在本文中，我们提出了一种概率主题模型，以推断特定生物学条件下 miRNA 和其靶 mRNA 的调控网络，即所谓的功能性 miRNA-mRNA 调控模块（FMRM）。本文中使用的概率模型可以有效地捕获特定细胞条件下 miRNA 和 mRNA 之间的关系。此外，该方法还分别识别了 EMT（上皮-间充质转化）数据集上皮、间充质和其他条件相关的负相关和正相关的 miRNA-mRNA 对。EMT 数据集上的结果表明，推断出的 FMRM 可以在转录后水平上潜在地构建“miRNA→mRNA→条件”的生物学链。
