ADRML: anticancer drug response prediction using manifold learning.

ABSTRACT: One of the prominent challenges in precision medicine is to select the most appropriate treatment strategy for each patient based on the personalized information. The availability of massive data about drugs and cell lines facilitates the possibility of proposing efficient computational models for predicting anticancer drug response. In this study, we propose ADRML, a model for Anticancer Drug Response Prediction using Manifold Learning to systematically integrate the cell line information with the drug information to make accurate predictions about drug therapeutic. The proposed model maps the drug response matrix into the lower-rank spaces that lead to obtaining new perspectives about cell lines and drugs. The drug response for a new cell line-drug pair is computed using the low-rank fea

SUBMITTER: Ahmadi Moughari F 

PROVIDER: S-EPMC7456328 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature