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Table 5 Calculated p-values for Wilcoxon signed rank sum tests (TM-score)

From: Benchmarking consensus model quality assessment for protein fold recognition

 

Method x

Method y

MODCHECK

ProQ-MX

ProQ-LG

ProQ*

ModSSEA

ModFOLD

Pcons*†

LEE*†

3D-Jury†

MODCHECK

 

0.33

0.10

9.21E-03

9.25E-04

6.54E-05

2.85E-05

3.80E-08

1.89E-12

ProQ-MX

0.67

 

4.04E-02

3.34E-03

1.49E-06

1.14E-07

1.83E-07

3.49E-09

1.42E-12

ProQ-LG

0.91

0.96

 

2.35E-02

5.82E-05

1.54E-05

2.51E-07

5.88E-09

4.31E-13

ProQ*

0.99

1.00

0.98

 

4.29E-02

1.15E-02

3.43E-05

2.67E-06

8.17E-11

ModSSEA

1.00

1.00

1.00

0.96

 

0.26

2.53E-02

5.08E-03

1.32E-07

ModFOLD

1.00

1.00

1.00

0.99

0.75

 

0.05

2.76E-02

3.15E-07

Pcons*†

1.00

1.00

1.00

1.00

0.98

0.95

 

0.38

1.07E-04

LEE*†

1.00

1.00

1.00

1.00

1.00

0.97

0.63

 

5.02E-05

3D-Jury†

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

 
  1. The different MQAP methods are compared in terms of the observed model quality of the top ranked models for each target. H0 = m x ≤ m y , H1 = m x > m y , where H0 is the null hypothesis; H1 is the alternative hypothesis; m x is the observed model quality of models selected by Method x and m y is the observed model quality of models selected by Method y according to the TM-score. * The MQAP scores for these methods were downloaded from CASP7 website; all other MQAP methods were run in house during the CASP7 experiment. † MQAP methods which rely on the comparison of multiple models or additional information from multiple servers; all other methods are capable of producing a single score based on a single model.