Table 1.

Features wise performance measures on disease and non-disease associated proteins dataset using deep neural network classifier

Primary sequence features
Features set	Vector length	P(+): N(−)	Sensitivity (%)	Specificity (%)	Accuracy (%)	PPV (%)	MCC	F1 score (%)	AUC
AAC	20	1: 1	86.32	53.31	70.09	66.04	0.43	74.34	0.755
PAAC	50	1: 1	86.32	53.31	70.09	66.04	0.43	74.34	0.755
CTD	343	1: 1	91.09	37.87	64.52	59.52	0.34	71.86	0.692
DC	400	1: 1	88.59	44.63	66.83	62.96	0.38	72.89	0.715
AAC_PAAC	70	1: 1	85.15	59.93	72.98	69.02	0.47	75.92	0.766
AAC_CTD	363	1: 1	87.45	47.18	67.74	62.83	0.39	72.81	0.709
AAC_DC	420	1: 1	83.55	52.72	68.73	64.66	0.39	72.69	0.708
PAAC_CTD	393	1: 1	88.52	45.23	67.02	62.46	0.39	72.78	0.720
PAAC_DC	450	1: 1	88.08	50.40	69.73	65.24	0.43	74.40	0.732
CTD_DC	743	1: 1	87.15	48.30	67.94	64.59	0.40	73.08	0.733
AAC_PAAC_CTD	413	1: 1	83.72	53.77	68.96	64.93	0.40	72.72	0.730
AAC_PAAC_DC	470	1: 1	86.32	52.49	69.86	65.64	0.43	74.09	0.729
AAC_CTD_DC	763	1: 1	90.22	45.17	67.88	62.69	0.40	73.72	0.729
PAAC_CTD_DC	793	1: 1	90.30	45.27	67.80	63.62	0.40	73.94	0.743
AAC_PAAC_CTD_DC	813	1: 1	87.50	49.44	68.50	64.00	0.41	73.50	0.739
Network Analyzer properties
Network properties	9	1: 1	78.24	90.51	84.43	89.22	0.69	83.24	0.858
Normalized And Filtered Network properties	6	1: 1	77.77	91.71	84.76	90.45	0.70	83.44	0.856

The notable performances are indicated by bold