Table 2

Model comparison results from simple network motifs.

data source

measure

SIM

RC

FF

FB


SIM

log p(Y | Mi)

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 | , Mi)

102.99

102.44

103.45

100.70

AIC

-197.98

-196.88

-196.9

-191.4


RC

log p(Y | Mi)

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 | , Mi)

47.18

101.22

100.46

97.62

AIC

-86.36

-194.44

-190.92

-185.24


FF

log p(Y | Mi)

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 | , Mi)

96.42

81.03

109.17

77.64

AIC

-184.84

-154.06

-208.34

-145.28


FB

log p(Y | Mi)

-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 | , Mi)

-1171.59

-1355.33

-1176.64

95.62

AIC

2351.2

2718.66

2363.26

-181.24


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 | , Mi), and Akaike's Information Criteria, or AIC.

Domedel-Puig et al. BMC Systems Biology 2010 4:18   doi:10.1186/1752-0509-4-18

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