Computational Inferring of Risk Subpathways Mediated by Dysfunctional Non-coding RNAs.

Abstract:

:Non-coding RNAs mediated core elements of pathways contributes to the disorder of biological function in diseases. Identification of non-coding RNAs mediated subpathways not only can help for deciphering the pathogenic mechanism of complex diseases, but also can gain insight into the functional roles of non-coding RNAs in human diseases. Here, we summarized the general steps for identifying non-coding RNA mediated subpathways and overviewed two of our previously developed methods, Subpathway-GMir and Subpathway-LNCE, which were designed to identify miRNAs and lncRNAs mediated risk subpathways respectively. We identified the key subpathway regions by integrating non-coding RNA-target gene associations, interesting genes and non-coding RNAs and pathway topologies. By applying methods to several disease datasets, we confirmed that our methods is effective in identifying risk subpathways and also can help uncover key non-coding RNAs in diseases. Additionally, reproducibility and robustness analysis demonstrated our methods are reliable.

journal_name

Adv Exp Med Biol

authors

Xu Y,Zhang Y,Li X

doi

10.1007/978-981-13-0719-5_9

subject

Has Abstract

pub_date

2018-01-01 00:00:00

pages

87-95

eissn

0065-2598

issn

2214-8019

journal_volume

1094

pub_type

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