RWRMTN

The misregulations of microRNA have been shown the contribution to diseases. Recently, we have proposed a computational method based on a random walk framework on a microRNA-target gene network to predict disease-associated microRNAs. This was shown superior when compared to existing state-of-the-art network- and machine learning-based methods since it well exploits mutual regulation between miRNAs and their target genes in microRNA-target gene networks.
To facilitate the use of this method, we develop a Cytoscape app, named RWRMTN, to predict disease-associated microRNAs. RWRMTN can work on any microRNA-target gene network. Highly ranked microRNAs can be supported with evidence from literature. Then, they can be also visualized based on the rankings in relationships with the query disease and their target genes. In addition, automation functions are also integrated, which permits RWRMTN can be used from external tools