autoHDR

Motivation:

Computational drug repositioning is nowadays a widely used approach for finding new uses of existing and experimental drugs. Network-based methods, which rely on the functional relationships between drugs, genes, proteins and diseases, have shown to be effective.

Results:

In this study, we implemented a state-of-the-art network-based method, random walk with restart algorithm on a heterogeneous network of drugs and diseases, as a tool for drug repositioning. The tool, HDR, is developed as an app in Cytoscape platform, thus it can exploit network integration and visualization functions of the platform. In addition, it can use both pre-installed and imported networks, thus makes user flexible in selecting datasets of interest. The ability of HDR was shown by comparing its overall prediction performance with some existing methods and by predicting novel drug-disease associations.

Availability:

HDR is distributed as a Cytoscape app, and can be downloaded freely at https://apps.cytoscape.org/apps/autohdr