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Hierarchical and Overlapping Co-Clustering of mRNA:miRNA Interactions

机译:mRNA:miRNA相互作用的层次和重叠共同簇

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microRNAs (miRNAs) are an important class of regulatory factors controlling gene expressions at post-transcriptional level. Studies on interactions between different miRNAs and their target genes are of utmost importance to understand the role of miRNAs in the control of biological processes. This paper contributes to these studies by proposing a method for the extraction of co-clusters of miRNAs and messenger RNAs (mRNAs). Different from several already available co-clustering algorithms, our approach efficiently extracts a set of possibly overlapping, exhaustive and hierarchically organized co-clusters. The algorithm is well-suited for the task at hand since: i) mRNAs and miRNAs can be involved in different regulatory networks that may or may not be co-active under some conditions, ii) exhaustive co-clusters guarantee that possible co-regulations are not lost, iii) hierarchical browsing of co-clusters facilitates biologists in the interpretation of results. Results on synthetic and on real human miRNA:mRNA data show the effectiveness of the approach.
机译:微小RNA(miRNA)是一类重要的调控因子,可在转录后水平控制基因表达。为了了解miRNA在生物过程控制中的作用,研究不同miRNA及其靶基因之间的相互作用至关重要。本文通过提出一种提取miRNA和Messenger RNA(mRNA)共簇的方法为这些研究做出了贡献。与几种已经可用的协同群集算法不同,我们的方法有效地提取了一组可能重叠,详尽且层次分明的协同群集。该算法非常适合手头的任务,因为:i)mRNA和miRNA可以参与不同的调节网络,这些调节网络在某些条件下可能具有协同作用,也可能不具有协同作用; ii)详尽的协同集群保证了可能的协同调节iii)共同小组的分级浏览有助于生物学家解释结果。合成和真实人类miRNA:mRNA数据的结果表明了该方法的有效性。

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