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Table 4 Goodness of fit of the simulations to the real experimental measurements under drug treatments

From: Generalized logical model based on network topology to capture the dynamical trends of cellular signaling pathways

  Control EGFR Control DNA damage Control Both
  input inhibitor input stimuli input drugs
AKT 0.64 0.81 –0.40 –0.54 0.75 0.93
ERK 0.32 0.40 –0.30 –0.39 0.19 0.23
S6 0.53 0.86 0.42 0.57 0.52 0.89
S6K 0.49 0.84 0.35 0.66 0.58 0.96
4EBP1 0.67 0.67 –0.33 -0.33 0.92 0.92
BIM 0.32 0.72 0.35 0.65 –0.15 –0.38
BID 0.30 0.37 0.03 0.03 0.16 0.16
JNK 0.02 –0.07 –0.47 –0.58 –0.06 0.01
p53 –0.04 –0.45 0.21 0.83 0.01 –0.09
CABL –0.45 –0.52 0.04 0.55 0.21 0.78
CHK –0.12 –0.18 –0.25 –0.28 –0.30 –0.69
CDC25 0.29 0.23 0.15 0.33 0.18 0.64
Casp8 0.06 –0.06 0.14 0.72 0.26 0.68
SMAC –0.05 0.08 –0.71 –0.87 0.48 0.99
  1. For example, the second column is the correlation coefficients between the simulations using control input (row 1 in Table 3) and the biological measurements treated with the drug that targets EGFR