Although drug combinations in cancer treatment appear to be a promising therapeutic
strategy with respect to monotherapy, it is arduous to discover new synergistic drug …

Compared to single-drug therapy, drug combinations have shown great potential in cancer
treatment. Most of the current methods employ genomic data and chemical information to …

Objective To develop an end-to-end deep learning framework based on a protein–protein
interaction (PPI) network to make synergistic anticancer drug combination predictions …

Drug combinations are frequently used for the treatment of cancer patients in order to
increase efficacy, decrease adverse side effects, or overcome drug resistance. Given the …

Drug combination therapies are superior to monotherapy for cancer treatment in many ways.
Identifying novel drug combinations by screening is challenging for the wet-lab experiments …

Identifying synergistic drug combinations is fundamentally important to treat a variety of
complex diseases while avoiding severe adverse drug–drug interactions. Although several …

Motivation Combination therapies have emerged as a treatment strategy for cancers to
reduce the probability of drug resistance and to improve outcomes. Large databases …

Motivation Drug combination therapy shows significant advantages over monotherapy in
cancer treatment. Since the combinational space is difficult to be traversed experimentally …

Identifying synergistic drug combinations (SDCs) is a great challenge due to the
combinatorial complexity and the fact that SDC is cell line specific. The existing …

Drug combination therapy has become a promising therapeutic strategy for cancer
treatment. While high-throughput drug combination screening is effective for identifying …