MSDRP: a deep learning model based on multisource data for predicting drug response.

ABSTRACT:

Motivation

Cancer heterogeneity drastically affects cancer therapeutic outcomes. Predicting drug response in vitro is expected to help formulate personalized therapy regimens. In recent years, several computational models based on machine learning and deep learning have been proposed to predict drug response in vitro. However, most of these methods capture drug features based on a single drug description (e.g. drug structure), without considering the relationships between drugs and biological entities (e.g. target, diseases, and side effects). Moreover, most of these methods collect features separately for drugs and cell lines but fail to consider the pairwise interactions between drugs and cell lines.

Results

In this paper, we propose a deep learning framework, named MSDRP

SUBMITTER: Zhao H 

PROVIDER: S-EPMC10474952 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature