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Table 5 Performance comparison with existing approaches for S-sulphenylation prediction on the independent test

From: SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models

Method

Sensitivity

Specificity

MCC

Accuracy

AUC

SOHPRED

0.73

0.74

0.34

N.A.b

0.80

PRESS

0.68

0.69

0.27

73.8%

N.A.

iSulf-Cys

0.73

0.64

0.31

66.8%

0.72

SulCysSite

0.77

0.71

N.A.

72.0%

0.76

SIMLIN

0.88

0.56

0.39

88.0%

0.82

MDD–SOHa

0.85

0.87

0.58

87.0%

N.A.

  1. aThe performance values of MDD-SOH were extracted from the study of Bui et al [6]
  2. bN.A.: not available
  3. The bold font shows the highest performance of each feature among the RF and SVM
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BMC Bioinformatics

ISSN: 1471-2105

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