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Identifying cancer-related microRNAs based on subpathways.

A new interesting article has been published in IET Syst Biol. 2018 Dec;12(6):273-278. doi: 10.1049/iet-syb.2018.5025. and titled:

Identifying cancer-related microRNAs based on subpathways.

Authors of this article are:

Liu W, Cui Z, Zan X.

A summary of the article is shown below:

MicroRNAs (miRNAs) are a class of small endogenous non-coding genes that play important roles in post-transcriptional regulation as well as other important biological processes. Accumulating evidence indicated that miRNAs were extensively involved in the pathology of cancer. However, determining which miRNAs are related to a specific cancer is problematic because one miRNA may target multiple genes and one gene may be targeted by multiple miRNAs. The authors proposed a new approach, named miR_SubPath, to identify cancer-associated miRNAs by three steps. The targeted genes were determined based on differentially expressed genes in significant dysfunctional subpathways. Then the candidate miRNAs were determined according to miRNA-genes associations. Finally, these candidate miRNAs were ranked based on their relations with some seed miRNAs in a functional similarity network. Results on real-world datasets showed that the proposed miR_SubPath method was more robust and could identify more cancer-related miRNAs than a prior approach, miR_Path, miR_Clust and Zhang’s method.

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