Random walks on mutual microRNA-target gene interaction network improve the prediction of disease-associated microRNAs.

ABSTRACT:

Background

MicroRNAs (miRNAs) have been shown to play an important role in pathological initiation, progression and maintenance. Because identification in the laboratory of disease-related miRNAs is not straightforward, numerous network-based methods have been developed to predict novel miRNAs in silico. Homogeneous networks (in which every node is a miRNA) based on the targets shared between miRNAs have been widely used to predict their role in disease phenotypes. Although such homogeneous networks can predict potential disease-associated miRNAs, they do not consider the roles of the target genes of the miRNAs. Here, we introduce a novel method based on a heterogeneous network that not only considers miRNAs but also the corresponding target genes in the network model.

Results</

SUBMITTER: Le DH 

PROVIDER: S-EPMC5686822 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature