Leveraging TCGA gene expression data to build predictive models for cancer drug response

Leveraging TCGA gene expression data to build predictive models for cancer drug response

Abstract Background Machine learning has been utilized to predict cancer drug response from multi-omics data generated from sensitivities of cancer cell lines to different therapeutic compounds. Here, we build machine learning models using gene expression data from patients’ primary tumor tissues to...

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Bibliographic Details
Main Authors: Evan A. Clayton, Toyya A. Pujol, John F. McDonald, Peng Qiu
Format: Article
Language:English
Published: BMC 2020-09-01
Series:BMC Bioinformatics
Subjects:
Personalized oncology
Machine learning
Drug response
Predictive models
Online Access:http://link.springer.com/article/10.1186/s12859-020-03690-4

Internet

http://link.springer.com/article/10.1186/s12859-020-03690-4

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