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• W2969264530 abstract "Pharmacogenomic responses to chemotherapy drugs can be modeled by supervised machine learning of expression and copy number of relevant gene combinations. Such biochemical evidence can form the basis of derived gene signatures using cell line data, which can subsequently be examined in patients that have been treated with the same drugs. These gene signatures typically contain elements of multiple biochemical pathways which together comprise multiple origins of drug resistance or sensitivity. The signatures can capture variation in these responses to the same drug among different patients." @default.
• W2969264530 created "2019-08-29" @default.
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• W2969264530 date "2019-09-01" @default.
• W2969264530 modified "2023-09-25" @default.
• W2969264530 title "Multigene signatures of responses to chemotherapy derived by biochemically-inspired machine learning" @default.
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• W2969264530 doi "https://doi.org/10.1016/j.ymgme.2019.08.005" @default.
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