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.
In this study, we developed network-based method, namely HDR, as an app of Cytoscape platform for drug repositioning. The task was approached in both drug- and disease-centric views. Besides, it can use both pre-installed and imported networks, thus makes the user flexible in selecting datasets of interest. In addition, predicted and existing associations between drugs and diseases as well as involved pathways/protein complexes/genes/targets can be visualized intuitively, thus supporting evidence for the predicted ones. The ability of HDR was also shown by comparing its overall prediction performance with some existing methods and by identifying drugs that can be repurposed for COVID-19 as well as potential diseases can be treated by Thalidomide.