Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

ABSTRACT: Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (

SUBMITTER: Huang C 

PROVIDER: S-EPMC5658085 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature