In total, four sets of models {fK1, fK2, fC1, fC2} were developed using four algorithms each (regularized, logistic, and regression and classification random forest), with predicted MEKi response compared to four observed MEKi response series {yK1, yK2, yC1, yC2}, with performance measured by two performance metrics (Spearman’s ρ and concordance index) for 128 pan-cancer performance measures (Fig 2B). The gene discussed is RBMS1; the disease is cancer.