DGPsubNet: Drug-Gene-Disease coherent SUBNETworks



Drug targets and disease genes may work as driver factors in transcriptional level, which propagate signals through gene regulatory network and cause the downstream genes' differential expression. How to analyze transcriptional response data to identify meaningful gene modules shared by both drugs and diseases is still a critical issue for molecular basis of drug-disease associations.


Here, we propose the drug-gene-disease coherent subnetwork concept to group the biological function related drugs, diseases, and genes. It was defined as the subnetwork with drug, gene, and disease as nodes and their interactions coherently crossing three layers as edges. Based on differential expression profiles of 418 drugs and 84 diseases, we develop a computational framework and identify 13 coherent subnetworks such as inflammatory bowel disease melanoma and melanoma inflammatory bowel disease relevant subnetwork. The results demonstrate that our coherent subnetwork approach is able to identify novel drug indications and highlight their molecular basis.


This version of the program is in very preliminary stage and provided just for testing purpose.