DIGREM: an integrated web-based platform for detecting effective multi-drug combinations


Abstract

Motivation: Synergistic drug combinations are a promising approach to achieve a desirable therapeutic effect in complex diseases through the multi-target mechanism. However, in vivo screening of all possible multi-drug combinations remains cost-prohibitive. An effective and robust computational model to predict drug synergy in silico will greatly facilitate this process.

Results: We developed DIGREM (Drug-Induced Genomic Response models for identification of Effective Multi-drug combinations), an online tool kit that can effectively predict drug synergy. DIGREM integrates DIGRE, IUPUI_CCBB, gene set-based and correlation-based models for users to predict synergistic drug combinations with dose-response information and drug-treated gene expression profiles.

Availability and implementation: http://lce.biohpc.swmed.edu/drugcombination.

Supplementary information: Supplementary data are available at Bioinformatics online.

Figures

Fig. 1.
Fig. 1.
(a) DIGRE model workflow: (1) Drug-treated gene expression and gene–gene interaction network are used to generate similarity scores (r); (2) combine r and dose–response curve to compute the genomic residual effect; (3) then the synergistic score is calculated and visualized. (b) DIGREM website analysis page interface
See this image and copyright information in PMC

Similar articles