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Genetic interactions and tissue specificity modulate the association of mutations with drug response
2019
Molecular Cancer Therapeutics
In oncology, biomarkers are widely used to predict subgroups of patients that respond to a given drug. Although clinical decisions often rely on single gene biomarkers, machine learning approaches tend to generate complex multi-gene biomarkers that are hard to interpret. Models predicting drug response based on multiple altered genes often assume that the effects of single alterations are independent. We asked whether the association of cancer driver mutations with drug response is modulated by
doi:10.1158/1535-7163.mct-19-0045
pmid:31826931
fatcat:khzvbjycafetnjp4zbv3zh2lhm