Ensembled machine learning framework for drug sensitivity prediction.

ABSTRACT: Drug sensitivity prediction is one of the critical tasks involved in drug designing and discovery. Recently several online databases and consortiums have contributed to providing open access to pharmacogenomic data. These databases have helped in developing computational approaches for drug sensitivity prediction. Cancer is a complex disease involving the heterogeneous behaviour of same tumour-type patients towards the same kind of drug therapy. Several methods have been proposed in the literature to predict drug sensitivity. However, these methods are not efficient enough to predict drug sensitivity. The present study has proposed an ensemble learning framework for drug-response prediction using a modified rotation forest. The proposed framework is further compared with three state-of-the

SUBMITTER: Sharma A 

PROVIDER: S-EPMC8687333 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature