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Pre-clinical models have been the workhorse of cancer research for decades. Albeit powerful, these models do not perfectly recapitulate the complexity of human tumors which has led to a disappointing bench-to-bedside attrition rate. The quest for biomarkers of drug response signatures has been particularly challenging, suffering from poor translatability from pre-clinical models to human tumors. To address this problem, we present a novel computational framework, PRECISE+, that employs non-doi:10.1101/2020.06.29.177139 fatcat:dr4k3izdzje3hoaqcemyta6uum