Table 3.

Over enhancers identification dataset and its independent test set performance comparison of the proposed and existing frameworks in terms of four evaluation measures

		5-Fold					Independent
	framework	ACC	Sn	Sp	MCC		ACC	Sn	Sp	MCC
Enhancers/ Non-Enhancer	iEnhancer-2L [33]	76.89	78.09	75.88	0.54		73	71	75	0.46
	EnhancerPred [31]	73.18	72.57	73.79	0.43		74	73.5	74.5	0.48
	tan2019ensemble [44]	74.83	73.25	76.42	0.49		-	-	-	-
	iEnhancer-DSNet [2]	76	76	76	0.52		78	78	77	0.56
	iEnhancer-Deep [16]	87.77	86.99	88.54	0.75		74.02	81.5	67	0.4902
	iEnhancer-EL [43]	78.03	75.67	80.39	0.56		74.75	71	78.5	0.496
	Rank-GAN [51]	75.25	74.87	75.63	0.5051		75.25	74.87	75.63	0.5051
	BERT [48]	76.2	79.5	73	0.525		75.6	80	71.2	0.514
	iEnhancer-XG [45]	58.55	75.7	86.5	0.62		75.75	74	77.5	0.514
	Tan et al. Enhancer [44]	74	73	76	0.5		76	76	76	0.51
	iEnhancer-ECNN [75]	-	-	-	-		76.9	78.5	75.2	0.537
	iEnhancer-EBLSTM [74]	-	-	-	-		77.2	75.5	79.5	0.534
	iEnhancer-CNN [65]	80.63	75.88	88.88	0.69		77.5	78.25	79	0.585
	iEnhancer-DCLA [52]	83.32	84.18	82.45	0.6668		78.25	78	78.5	0.565
	iEnhancer-GAN [36]	-	-	-	-		78.4	81.1	75.8	0.567
	Enhancer-RD [36]	-	-	-	-		78.8	81	76.5	0.576
	iEnhancer-5Step [37]	82.3	81.1	83.5	0.65		79	82	76	0.58
	iEnhacner-BERT [47]	79.4	-	-	0.593		79.3	-	-	0.585
	iEnhancer-MRBF [53]	81.23	79.52	82.95	0.6254		79.75	82.00	77.50	0.5956
	Proposed	94.6	94.6	94.9	0.892		84.3	84.2	87	0.686