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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6513155 | PMC |
| http://dx.doi.org/10.1093/bioinformatics/bty860 | DOI Listing |
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