Computer-aided prediction of antigen presenting cell modulators for designing peptide-based vaccine adjuvants

Nagpal, Gandharva; Chaudhary, Kumardeep; Agrawal, Piyush; Raghava, Gajendra P. S.

doi:10.1186/s12967-018-1560-1

Journal of Translational Medicine

Table 2 The performance of SVM-based models developed using various features; models were evaluated on independent dataset (external cross-validation)

From: Computer-aided prediction of antigen presenting cell modulators for designing peptide-based vaccine adjuvants

Features	Threshold	Sensitivity (%)	Specificity (%)	Accuracy (%)	MCC	AUROC	Parameters
AAC*	− 0.1	94.10 ± 2.70	93.77 ± 3.28	93.91 ± 2.00	0.88 ± 0.03	0.98 ± 0.00	g = 0.001, c = 3, j = 3
N5 AAC	0	89.75 ± 3.61	90.88 ± 3.67	90.32 ± 2.27	0.81 ± 0.04	0.95 ± 0.01	g = 0.0005, c = 2, j = 1
C5 AAC	0	91.12 ± 3.53	91.64 ± 2.90	91.40 ± 2.13	0.83 ± 0.04	0.97 ± 0.01	g = 0.001, c = 9, j = 1
N5C5 AAC	− 0.2	94.61 ± 3.35	93.59 ± 3.23	94.07 ± 2.16	0.88 ± 0.04	0.98 ± 0.00	g = 0.0005, c = 1, j = 1
DPC	0	93.77 ± 2.76	95.32 ± 1.40	94.64 ± 1.24	0.89 ± 0.02	0.99 ± 0.00	g = 0.0005, c = 1, j = 2
N5 DPC	− 0.1	81.68 ± 4.25	87.36 ± 2.78	84.62 ± 2.65	0.69 ± 0.05	0.93 ± 0.01	g = 1e−05, c = 9, j = 1
C5 DPC	− 0.1	92.31 ± 3.36	94.71 ± 2.45	93.55 ± 1.40	0.87 ± 0.02	0.98 ± 0.01	g = 0.0005, c = 1, j = 2
N5C5 DPC	− 0.2	94.10 ± 3.06	93.75 ± 2.33	93.90 ± 1.49	0.88 ± 0.03	0.98 ± 0.01	g = 0.0001, c = 1, j = 1
N5 bin	− 0.1	88.46 ± 2.90	89.43 ± 3.32	88.98 ± 2.36	0.78 ± 0.04	0.95 ± 0.01	g = 0.5, c = 2, j = 1
C5 bin	− 0.2	93.70 ± 3.03	87.88 ± 4.25	90.63 ± 2.43	0.82 ± 0.04	0.97 ± 0.01	g = 0.5, c = 1, j = 2
N5C5 bin	0.2	90.95 ± 3.18	91.13 ± 3.44	91.03 ± 2.77	0.82 ± 0.05	0.97 ± 0.01	g = 0.05, c = 1, j = 4
N10 bin	− 0.2	89.38 ± 6.68	90.46 ± 4.67	90.01 ± 3.26	0.79 ± 0.06	0.95 ± 0.03	g = 0.1, c = 2, j = 2
C10 bin	− 0.2	85.02 ± 8.02	85.24 ± 5.15	85.19 ± 4.09	0.69 ± 0.09	0.93 ± 0.03	g = 0.05, c = 3, j = 1
N10C10 bin	− 0.4	88.73 ± 5.95	92.33 ± 5.69	91.04 ± 2.52	0.81 ± 0.05	0.97 ± 0.02	g = 0.1, c = 1, j = 1
AAC + motif	− 0.1	93.11 ± 1.86	95.33 ± 3.13	94.35 ± 1.67	0.89 ± 0.03	0.99 ± 0.00	g = 0.001, c = 6, j = 1
DPC + motif	0	93.28 ± 2.38	96.36 ± 1.70	95.00 ± 1.25	0.90 ± 0.02	0.99 ± 0.00	g = 0.0005, c = 1, j = 2

This table shows average performance (mean ± standard deviation) of models on randomly generated independent datasets (bagging)
MCC Matthews correlation coefficient, AAC amino acid composition, DPC dipeptide composition, N5 first 5 residues from N terminus, C5 first 5 residues from C terminus, N5C5 first 5 residues from N and C terminus respectively, bin binary profile, AAC + motif amino acid composition with MERCI motif score, DPC + motif dipeptide composition with MERCI motif score, SVM parameters g gamma parameter of the radial basis function, , c trade-off between training error and margin, j regularization parameter (cost-factor, by which training errors on positive examples outweigh errors on negative examples)

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ISSN: 1479-5876

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