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Table 1 The performance of SVM models using amino acid compositions of whole peptides and five residues of N-terminus. Last column shows performance of binary-based SVM model using first five residues of peptides.

From: Analysis and prediction of antibacterial peptides

  Whole Peptide Composition 5 N-terminal residue Composition 5 N-terminal binary Pattern
Threshold Sen. Spec. Acc. Sen. Spec. Acc. Sen. Spec. Acc.
-1 98.15 60.45 80.13 97.31 25.45 61.38 95.81 24.25 60.03
-0.9 97.94 63.60 81.53 95.21 30.54 62.87 94.31 30.54 62.43
-0.8 97.53 67.19 83.03 93.71 35.33 64.52 93.71 37.13 65.42
-0.7 97.12 70.56 84.43 91.62 39.82 65.72 91.62 43.11 67.37
-0.6 96.91 72.81 85.39 90.42 46.11 68.26 90.12 48.50 69.31
-0.5 96.30 76.18 86.68 89.22 50.60 69.91 86.83 54.19 70.51
-0.4 95.88 77.53 87.11 87.72 55.09 71.41 85.03 59.88 72.46
-0.3 94.65 80.90 88.08 84.73 58.98 71.86 82.34 64.97 73.65
-0.2 93.42 84.27 89.04 81.44 63.47 72.46 80.24 68.86 74.55
0 89.92 88.09 89.04 73.65 72.75 73.20 74.25 74.85 74.55
0.1 88.48 89.44 88.94 70.36 76.65 73.50 70.66 77.54 74.10
0.2 86.63 90.56 88.51 66.77 79.64 73.20 67.96 83.83 75.90
0.3 84.98 91.01 87.86 63.47 83.83 73.65 64.97 88.32 76.65
0.4 83.74 93.03 88.18 57.49 86.83 72.16 60.78 88.92 74.85
0.5 80.04 93.26 86.36 53.59 89.52 71.56 57.78 90.12 73.95
0.6 77.37 94.83 85.71 48.50 91.62 70.06 54.49 91.02 72.75
0.7 75.51 95.28 84.96 44.61 94.01 69.31 51.50 93.41 72.46
0.8 72.02 95.28 83.14 39.22 94.91 67.07 44.91 95.51 70.21
0.9 67.90 96.40 81.53 34.43 96.11 65.27 39.52 96.11 67.81
1 64.61 97.53 80.34 29.04 97.90 63.47 32.34 97.01 64.67