Incorporating support vector machine with sequential minimal optimization to identify anticancer peptides

BMC Bioinformatics

Table 5 Comparison of my models and some existing tools

Datasets	Tool	Sensitivity	Specificity	Accuracy	MCC
Positive + negative 1	SMO-1	0.850	0.860	0.855	0.710
	AntiCP-1	1	0	0.500	–
	mACPpred	0.95	0.42	0.685	0.436
	ACPred	0.930	0.330	0.630	0.325
	ACPred-Fuse	0.820	0.870	0.845	0.691
	ACPred-FL	0.88	0.39	0.635	0.310
Positive + negative 2	SMO-2	0.970	0.948	0.952	0.847
	AntiCP-2	0.91	0.88	0.895	0.790
	mACPpred	0.949	0.790	0.815	0.583
	ACPred	0.930	0.724	0.758	0.501
	ACPred-Fuse	0.820	0.836	0.833	0.549
	ACPred-FL	0.880	0.024	0.167	− 0.183

ISSN: 1471-2105