Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance
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.
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-05-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-22989-1 |