RWRMTN: a tool for predicting disease-associated microRNAs based on a microRNA-target gene network.

ABSTRACT:

Background

The misregulation of microRNA (miRNA) has been shown to cause diseases. Recently, we have proposed a computational method based on a random walk framework on a miRNA-target gene network to predict disease-associated miRNAs. The prediction performance of our method is better than that of some existing state-of-the-art network- and machine learning-based methods since it exploits the mutual regulation between miRNAs and their target genes in the miRNA-target gene interaction networks.

Results

To facilitate the use of this method, we have developed a Cytoscape app, named RWRMTN, to predict disease-associated miRNAs. RWRMTN can work on any miRNA-target gene network. Highly ranked miRNAs are supported with evidence from the literature. They then can also be visualized

SUBMITTER: Le DH 

PROVIDER: S-EPMC7296691 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature