Topologically inferring active miRNA-mediated subpathways toward precise cancer classification by directed random walk.

ABSTRACT: Accurate predictions of classification biomarkers and disease status are indispensable for clinical cancer diagnosis and research. However, the robustness of conventional gene biomarkers is limited by issues with reproducibility across different measurement platforms and cohorts of patients. In this study, we collected 4775 samples from 12 different cancer datasets, which contained 4636 TCGA samples and 139 GEO samples. A new method was developed to detect miRNA-mediated subpathway activities by using directed random walk (miDRW). To calculate the activity of each miRNA-mediated subpathway, we constructed a global directed pathway network (GDPN) with genes as nodes. We then identified miRNAs with expression levels which were strongly inversely correlated with differentially expressed targe

SUBMITTER: Ning Z 

PROVIDER: S-EPMC6763789 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature