Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance

Abstract

Personalized prediction of tumor radiosensitivity would facilitate development of precision medicine workflows for cancer treatment. Here, the authors integrate machine learning and genome-scale metabolic modeling approaches to identify multi-omics biomarkers predictive of radiation response.