Prediction of Protein-Protein Interactions from Protein Sequences by Combining MatPCA Feature Extraction Algorithms and Weighted Sparse Representation Models

Table 7

Performance comparison of other methods on the yeast dataset.

Model	Test set	ACC (%)	PE (%)	SN (%)	MCC (%)
Zhou et al.’s work [42]	LD + SVM	88.56 ± 0.33	89.50 ± 0.60	87.37 ± 0.22	77.15 ± 0.68
Guo et al.’s work [22]	AC	87.36 ± 1.38	87.82 ± 4.33	87.30 ± 4.68	N/A
	ACC	89.33 ± 2.67	88.87 ± 6.16	89.93 ± 3.68	N/A
You et al.’s work [23]	PCA-EELM	87.00 ± 0.29	87.59 ± 0.32	86.15 ± 0.43	77.36 ± 0.44
Yang et al.’s work [43]	Cod1	75.08 ± 1.13	74.75 ± 1.23	75.81 ± 1.20	N/A
	Cod2	80.04 ± 1.06	82.17 ± 1.35	76.77 ± 0.69	N/A
	Cod3	80.41 ± 0.47	81.86 ± 0.99	78.14 ± 0.90	N/A
	Cod4	86.15 ± 1.17	90.24 ± 1.34	81.03 ± 1.74	N/A
Proposed method	MatPCA + WSRC	94.55 ± 0.63	92.33 ± 0.91	97.15 ± 0.42	89.68 ± 1.12