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Table 3 Performance evaluation (auROC and auPRC scores) of four different methods on a subset of the genome-wide cress and human datasets.

From: Accurate splice site prediction using support vector machines

 

SM

WD

WDSP

WDS

WDSSP

Cress

     

   Acceptor

     

   auROC

99.41

98.97

99.36

99.43

99.43

   auPRC

91.76

84.24

90.64

92.01

92.09

   Donor

     

   auROC

99.59

99.38

99.58

99.61

99.61

   auPRC

93.34

88.62

93.42

93.68

93.87

Human

     

   Acceptor

     

   auROC

97.72

97.34

97.71

97.73

97.82

   auPRC

50.39

42.77

50.48

51.78

54.12

   Donor

     

   auROC

98.44

98.36

98.36

98.51

98.37

   auPRC

53.29

46.53

54.06

53.08

54.69

  1. The methods compared are SpliceMachine (SM), the weighted degree kernel (WD), the weighted degree kernel complemented with six spectrum kernels (WDSP), the weighted degree kernel with shifts (WDS), and the weighted degree kernel with shifts complemented by six spectrum kernels (WDSSP).
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BMC Bioinformatics

ISSN: 1471-2105

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