Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients

Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. Here, the authors present a machine-learning framework to identify robust drug biomarkers by taking advantage of network-based analyses using pharmacogenomic data...

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Autores principales: JungHo Kong, Heetak Lee, Donghyo Kim, Seong Kyu Han, Doyeon Ha, Kunyoo Shin, Sanguk Kim
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/bc2d4c908ac14d54ad3b9ed62cdef10f
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Sumario:Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. Here, the authors present a machine-learning framework to identify robust drug biomarkers by taking advantage of network-based analyses using pharmacogenomic data.