Predicting Anticancer Drug Response With Deep Learning Constrained by Signaling Pathways.

ABSTRACT: Thanks to the availability of multiomics data of individual cancer patients, precision medicine or personalized medicine is becoming a promising treatment for individual cancer patients. However, the association patterns, that is, the mechanism of response (MoR) between large-scale multiomics features and drug response are complex and heterogeneous and remain unclear. Although there are existing computational models for predicting drug response using the high-dimensional multiomics features, it remains challenging to uncover the complex molecular mechanism of drug responses. To reduce the number of predictors/features and make the model more interpretable, in this study, 46 signaling pathways were used to build a deep learning model constrained by signaling pathways, consDeepSignaling, for

SUBMITTER: Zhang H 

PROVIDER: S-EPMC9581064 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature