Predicting synergistic anticancer drug combination based on low-rank global attention mechanism and bilinear predictor.

ABSTRACT:

Motivation

Drug combination therapy has exhibited remarkable therapeutic efficacy and has gradually become a promising clinical treatment strategy of complex diseases such as cancers. As the related databases keep expanding, computational methods based on deep learning model have become powerful tools to predict synergistic drug combinations. However, predicting effective synergistic drug combinations is still a challenge due to the high complexity of drug combinations, the lack of biological interpretability, and the large discrepancy in the response of drug combinations in vivo and in vitro biological systems.

Results

Here, we propose DGSSynADR, a new deep learning method based on global structured features of drugs and targets for predicting synergistic anticancer drug co

SUBMITTER: Gan Y 

PROVIDER: S-EPMC10598574 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature