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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.