LipoFNT: Lipoylation Sites Identification with Flexible Neural Tree

Table 1

The Performances of Different Features.

Features	Sn(%)	Sp(%)	Acc(%)	F1	MCC
Binary Encoding	56.36	75.80	66.08	0.6243	0.3279
AA Composition	64.84	62.79	63.82	0.6418	0.2764
Grouping AA Composition	71.78	72.04	71.91	0.7187	0.4382
Physicochemical Properties	75.53	73.93	74.73	0.7493	0.4947
KNN Features	74.94	65.85	70.40	0.7168	0.4096
Secondary Tendency Structure	69.96	77.40	73.68	0.7266	0.4749
PSSM	71.20	79.39	75.30	0.7424	0.5076
BPB	72.81	78.51	75.66	0.7495	0.5140
Bi-gram	75.17	76.81	75.99	0.7579	0.5199
Tri-gram	77.28	78.27	77.78	0.7766	0.5555
Proposed Algorithm	81.07	80.29	80.68	0.8076	0.6136