Positive-unlabelled learning of glycosylation sites in the human proteome

Li, Fuyi; Zhang, Yang; Purcell, Anthony W.; Webb, Geoffrey I.; Chou, Kuo-Chen; Lithgow, Trevor; Li, Chen; Song, Jiangning

doi:10.1186/s12859-019-2700-1

BMC Bioinformatics

Table 5 Performance comparison of PU-learning, supervised-learning, and one-class classification algorithms on the test datasets

From: Positive-unlabelled learning of glycosylation sites in the human proteome

Type	Algorithm	2007			2010			2013
Type	Algorithm	F1	ACC	AUC	F1	ACC	AUC	F1	ACC	AUC
N	PA2DE (V2.0)	0.935 ± 0.003	0.934 ± 0.004	0.949 ± 0.007	0.933 ± 0.001	0.932 ± 0.002	0.950 ± 0.005	0.962 ± 0.011	0.963 ± 0.007	0.997 ± 0.008
	PA2DE	0.930 ± 0.002	0.928 ± 0.002	0.943 ± 0.004	0.930 ± 0.002	0.929 ± 0.003	0.947 ± 0.003	0.951 ± 0.018	0.952 ± 0.017	0.996 ± 0.002
	PAODE	0.929 ± 0.013	0.928 ± 0.010	0.958 ± 0.013	0.922 ± 0.051	0.923 ± 0.035	0.950 ± 0.010	0.931 ± 0.002	0.929 ± 0.003	0.950 ± 0.008
	PNB	0.929 ± 0.004	0.928 ± 0.004	0.950 ± 0.013	0.896 ± 0.074	0.887 ± 0.094	0.954 ± 0.070	0.931 ± 0.003	0.929 ± 0.003	0.955 ± 0.011
	PTAN	0.916 ± 0.013	0.913 ± 0.015	0.933 ± 0.004	0.876 ± 0.019	0.860 ± 0.024	0.938 ± 0.006	0.875 ± 0.019	0.859 ± 0.024	0.941 ± 0.003
	PFBC	0.910 ± 0.016	0.904 ± 0.018	0.939 ± 0.004	0.930 ± 0.004	0.928 ± 0.005	0.955 ± 0.012	0.893 ± 0.076	0.882 ± 0.096	0.939 ± 0.088
	RF^[a]	0.924 ± 0.018	0.929 ± 0.016	0.994 ± 0.004	0.922 ± 0.039	0.923 ± 0.035	0.950 ± 0.010	0.931 ± 0.002	0.929 ± 0.003	0.947 ± 0.003
	SVM	0.919 ± 0.002	0.907 ± 0.002	0.935 ± 0.002	0.904 ± 0.002	0.897 ± 0.003	0.929 ± 0.003	0.931 ± 0.002	0.929 ± 0.003	0.929 ± 0.003
	O-SVM^[b]	0.683 ± 0.009	0.740 ± 0.011	0.740 ± 0.011	0.689 ± 0.010	0.748 ± 0.012	0.748 ± 0.012	0.689 ± 0.010	0.747 ± 0.012	0.747 ± 0.012
	O-Classifier^[c]	0.820 ± 0.032	0.847 ± 0.023	0.847 ± 0.023	0.849 ± 0.029	0.865 ± 0.023	0.865 ± 0.023	0.836 ± 0.029	0.857 ± 0.021	0.857 ± 0.021
O	PA2DE (V2.0)	0.933 ± 0.046	0.930 ± 0.053	0.986 ± 0.010	0.945 ± 0.021	0.943 ± 0.014	0.995 ± 0.012	0.986 ± 0.013	0.986 ± 0.020	0.997 ± 0.031
	PA2DE	0.928 ± 0.052	0.924 ± 0.060	0.978 ± 0.022	0.932 ± 0.018	0.928 ± 0.050	0.981 ± 0.019	0.974 ± 0.019	0.974 ± 0.019	0.994 ± 0.006
	PAODE	0.848 ± 0.061	0.816 ± 0.090	0.976 ± 0.006	0.923 ± 0.017	0.926 ± 0.014	0.984 ± 0.019	0.952 ± 0.015	0.955 ± 0.013	0.996 ± 0.007
	PNB	0.906 ± 0.030	0.896 ± 0.036	0.989 ± 0.002	0.926 ± 0.017	0.921 ± 0.020	0.991 ± 0.002	0.970 ± 0.012	0.969 ± 0.012	0.997 ± 0.001
	PTAN	0.798 ± 0.075	0.832 ± 0.051	0.961 ± 0.011	0.844 ± 0.044	0.815 ± 0.067	0.924 ± 0.052	0.886 ± 0.064	0.867 ± 0.090	0.972 ± 0.035
	PFBC	0.838 ± 0.046	0.810 ± 0.070	0.916 ± 0.057	0.910 ± 0.031	0.901 ± 0.038	0.990 ± 0.002	0.904 ± 0.073	0.886 ± 0.103	0.991 ± 0.004
	RF^[a]	0.914 ± 0.019	0.919 ± 0.016	0.984 ± 0.015	0.923 ± 0.017	0.926 ± 0.014	0.984 ± 0.019	0.952 ± 0.015	0.955 ± 0.013	0.996 ± 0.007
	SVM	0.924 ± 0.014	0.919 ± 0.016	0.988 ± 0.002	0.930 ± 0.008	0.975 ± 0.009	0.975 ± 0.009	0.920 ± 0.019	0.924 ± 0.020	0.974 ± 0.001
	O-SVM^[b]	0.677 ± 0.016	0.537 ± 0.033	0.537 ± 0.033	0.661 ± 0.006	0.506 ± 0.012	0.506 ± 0.012	0.665 ± 0.007	0.007 ± 0.016	0.506 ± 0.016
	O-Classifier^[c]	0.141 ± 0.141	0.529 ± 0.033	0.529 ± 0.033	0.135 ± 0.100	0.532 ± 0.025	0.532 ± 0.025	0.144 ± 0.116	0.527 ± 0.035	0.527 ± 0.035

[a] RF – Random Forest; [b] O-SVM – One-class SVM; [c] O-Classifier – One-class Classifier

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