Using Weighted Sparse Representation Model Combined with Discrete Cosine Transformation to Predict Protein-Protein Interactions from Protein Sequence

Table 6

Performance comparison of different methods on the Yeast dataset.

Model	Test set	Accu. (%)	Prec. (%)	Sen. (%)	MCC (%)
Guos’ work [25]	ACC	89.33 ± 2.67	88.87 ± 6.16	89.93 ± 3.68	N/A
	AC	87.36 ± 1.38	87.82 ± 4.33	87.30 ± 4.68	N/A
Zhous’ work [26]	SVM + LD	88.56 ± 0.33	89.50 ± 0.60	87.37 ± 0.22	77.15 ± 0.68
Yangs’ work [27]	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
Wongs’ work [28]	RF + PR-LPQ	93.92 ± 0.36	96.45 ± 0.45	91.10 ± 0.31	88.56 ± 0.63
Yous’ work [29]	PCA-EELM	87.00 ± 0.29	87.59 ± 0.32	86.15 ± 0.43	77.36 ± 0.44
Proposed method	WSRC	96.28 ± 0.52	99.92 ± 0.18	92.64 ± 1.00	92.82 ± 0.97