Table 2.

AUC of logistic regression model to predict synergistic combinations: GSEA-based expression similarity scores

	Merged	6 h, IC20 (48 h)	6 h, IC20 (24 h)	12 h, IC20 (48 h)	12 h, IC20 (24 h)	24 h, IC20 (48 h)	24 h, IC20 (24 h)
p=q=5000	0.65 [0.73]	0.51 [0.72]	0.74 [0.78]	0.46 [0.71]	0.66 [0.76]	0.64 [0.74]	0.65 [0.73]
p=q=2000	0.66 [0.74]	0.52 [0.72]	0.75 [0.79]	0.43 [0.71]	0.65 [0.76]	0.67 [0.75]	0.65 [0.73]
p=q=1000	0.66 [0.74]	0.55 [0.72]	0.76 [0.79]	0.42 [0.71]	0.65 [0.75]	0.68 [0.75]	0.66 [0.74]
p=q=500	0.65 [0.74]	0.57 [0.72]	0.77 [0.79]	0.42 [0.71]	0.65 [0.75]	0.68 [0.75]	0.66 [0.74]

AUCs are shown using gene expression similarity only and combining gene expression similarity with structural similarity (in brackets).