Table 3.

AUROC and AUPRC results achieved on the independent test set across deep learning classification models

	AUROC			AUPRC
Family	Seq-CNN	EMBER (BCE)	EMBER (PBCE)	Seq-CNN	EMBER (BCE)	EMBER (PBCE)
Akt	0.828	0.858	0.881	0.327	0.323	0.423
CDK	0.906	0.917	0.925	0.648	0.696	0.698
CK2	0.900	0.914	0.923	0.722	0.780	0.788
MAPK	0.887	0.899	0.896	0.665	0.694	0.697
PIKK	0.871	0.886	0.913	0.586	0.611	0.670
PKA	0.846	0.868	0.877	0.636	0.680	0.705
PKC	0.873	0.895	0.902	0.735	0.774	0.798
Src	0.997	0.994	0.996	0.992	0.992	0.994
Macro-average	0.889	0.904	0.914	0.664	0.694	0.722
Micro-average	0.913	0.926	0.932	0.731	0.763	0.784

Notes: The AUROC and AUPRC are presented per kinase family for each model. From left to right, we include results for the ablated sequence-only CNN, EMBER trained using a canonical BCE loss, and EMBER trained using the kinase phylogeny-weighted loss as described in Section 3.