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Table 2 Model comparison results from simple network motifs.

From: Statistical model comparison applied to common network motifs

data source

measure

SIM

RC

FF

FB

SIM

log p(Y | M i )

89.3

73.74

89.6

49.03

 

DIC

-198.1

-192.5

-198.8

-177.51

 

pD

3.93

2.94

4.01

4.34

 

log p(Y | , M i )

102.99

102.44

103.45

100.70

 

AIC

-197.98

-196.88

-196.9

-191.4

RC

log p(Y | M i )

29.21

87.61

73.58

55.38

 

DIC

-86.17

-194.60

-187.13

-175.21

 

pD

4.08

3.92

4.53

4.66

 

log p(Y | , M i )

47.18

101.22

100.46

97.62

 

AIC

-86.36

-194.44

-190.92

-185.24

FF

log p(Y | M i )

80.20

57.60

93.43

22.95

 

DIC

-184.7

-153.1

-208.8

-131.53

 

pD

4.06

3.92

4.81

5.01

 

log p(Y | , M i )

96.42

81.03

109.17

77.64

 

AIC

-184.84

-154.06

-208.34

-145.28

FB

log p(Y | M i )

-17.60

-13.93

-39.68

79.07

 

DIC

2351.3

2718.1

2375.8

-181.37

 

pD

4.04

3.66

4.61

4.98

 

log p(Y | , M i )

-1171.59

-1355.33

-1176.64

95.62

 

AIC

2351.2

2718.66

2363.26

-181.24

  1. Model comparison results for artificial data from the simple ODE models SIM, RC, FF (type 1 coherent with OR gate) and negative FB motifs. Each fit is assessed in terms of model evidence, log p(Y | Mi), the deviance information criteria, or DIC, the effective degrees of freedom, or pD, the maximum likelihood value obtained from MCMC simulations, log p(Y | , M i ), and Akaike's Information Criteria, or AIC.