Table 2

Classification result of peptide-encoding schemes
Method # of features 10-fold cross validation on training dataset only Holdout method using training dataset and testing dataset
sens spec F1 ACC AUC sens spec F1 ACC AUC
EpicCapo 360
    0.883
 ± 0.005
0.792 ± 0.006
    0.886
 ± 0.003
0.841 ± 0.004 0.915 ± 0.001 0.883 0.744
    0.831
0.815
    0.882
EpicCapo(3 AAPPs*) 27 0.876 ± 0.005
    0.821
 ± 0.005
0.862 ± 0.003
    0.848
 ± 0.003
    0.916
 ± 0.001
0.855
    0.777
0.828
    0.817
0.878
DPPS 90 0.865 ± 0.005 0.760 ± 0.007 0.834 ± 0.004 0.816 ± 0.004 0.888 ± 0.001 0.868 0.697 0.807 0.785 0.878
FASGAI 54 0.847 ± 0.004 0.761 ± 0.004 0.825 ± 0.003 0.801 ± 0.003 0.882 ± 0.001 0.840 0.730 0.803 0.787 0.874
z-scale 45 0.847 ± 0.005 0.732 ± 0.005 0.815 ± 0.004 0.793 ± 0.004 0.873 ± 0.002 0.848 0.676 0.788 0.765 0.858
ISA/ECI 18 0.799 ± 0.005 0.652 ± 0.005 0.760 ± 0.003 0.731 ± 0.003 0.797 ± 0.001 0.829 0.643 0.766 0.739 0.796
Binary encoding 180
    0.883
 ± 0.005
0.721 ± 0.006 0.831 ± 0.003 0.807 ± 0.003 0.883 ± 0.002
    0.887
0.705 0.820 0.799 0.879

Means and standard deviations were calculated by 20 iterations of 10-fold cross validation.

Underlined values represent the highest performance.

sens = sensitivity; spec = specificity; F1 = F-score; ACC = accuracy; AUC = area under the curve.

*These three top-ranked AAPPs were MICC010101, SIMK990101, and SIMK990105 (see Additional file 1).

Saethang et al.

Saethang et al. BMC Bioinformatics 2012 13:313   doi:10.1186/1471-2105-13-313

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