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Table 4 The prediction performance of Scansite, NetPhosK, KinasePhos and GPS for four well-studied PKs of PKA, CK2, ATM and S6K.

From: PPSP: prediction of PK-specific phosphorylation site with Bayesian decision theory

 

PK Group

PKA

CK2

ATM

S6K

Predictor

 

Sn(%)

Sp(%)

MCC

Sn(%)

Sp(%)

MCC

Sn(%)

Sp(%)

MCC

Sn(%)

Sp(%)

MCC

PPSP

Defaulta

90.11

91.7

0.3841

83.21

90.01

0.3596

93.02

94.06

0.4627

92.85

97.97

0.6618

ScanSite

Highb

21.98

99.96

0.4450

10.95

99.86

0.2655

18.6

99.8

0.3443

N/A

N/A

N/A

 

Medium

44.51

99.39

0.5084

27.01

99.11

0.3342

25.58

98.89

0.2756

N/A

N/A

N/A

 

Low

47.8

98.29

0.4041

54.02

96.34

0.3684

51.16

94.89

0.2739

N/A

N/A

N/A

NetPhosK

Default

79.12

90.65

0.3165

82.48

89.43

0.3464

86.01

98.51

0.6786

82.35

97.14

0.5404

KinasePhos

90% (Sp)d

90.72

91.3

0.3783

72.53

91.58

0.3384

88.37

87.8

0.3137

N/A

N/A

N/A

 

95% (Sp)

89.18

94.62

0.4595

64.58

94.93

0.3806

88.37

92.14

0.3893

N/A

N/A

N/A

 

100% (Sp)

76.8

98.47

0.6154

54.86

98.66

0.5222

86.05

96.89

0.5497

N/A

N/A

N/A

GPS

Default

88.88

90.57

0.3564

82.99

87.59

0.3210

90.86

89.55

0.3498

94.9

91.34

0.3964

  1. a. The default parameters are employed for PPSP, NetPhosK and GPS.
  2. b. ScanSite 2.0 has three thresholds for prediction, including high, medium and low stringencies.
  3. c. N/A – not available.
  4. d. KinasePhos has paid attention to prediction specificity with three cut-off values, as 90%, 95% and 100%.