Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes
Abstract
The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning...
Paper Details
Title
Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes
Published Date
Feb 24, 2017
Journal
Volume
7
Issue
1
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