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Table 2 Parameters values with noisy data (one experiment)

From: Identification of regulatory structure and kinetic parameters of biochemical networks via mixed-integer dynamic optimization

   10%   
  Profile 1 Profile 2 Profile 3 Profile 4
f 13 -0.14 -0.27 -0.84 -0.79
f 21 0.26 0.47 0.4 0.29
f 32 0.44 1 0.64 0.41
f 41 0.04 0 0.9 1
f 53 0 0.26 0.42 0.12
f 54 -0.06 0.04 0.1 -0.12
f 64 0.13 0.07 1 1
Residual 1.88 1.67 1.68 2.29
   5%   
  Profile 5 Profile 6 Profile 7 Profile 8
f 13 -0.282 -0.532 -0.631 -0.893
f 21 0.56 0.618 0.306 0.6
f 32 1 1 0.436 1
f 41 0 0.092 0.761 0.742
f 53 0.368 0.639 0.273 0.298
f 54 0.127 0.244 0.021 0.279
f 64 0.064 0.158 1 1
Residual 0.4128 0.4203 0.5706 0.4482
   1%   
  Profile 9 Profile 10 Profile 11 Profile 12
f 13 -0.881 -0.427 -0.859 -0.71
f 21 0.571 0.523 0.5 0.414
f 32 0.885 0.809 0.758 0.608
f 41 0.587 0.078 0.661 0.656
f 53 0.479 0.467 0.507 0.402
f 54 0.2 0.176 0.197 0.136
f 64 1 0.162 1 1
Residual 0.0207 0.0163 0.0167 0.0227
   0.5%   
  Profile 13 Profile 14 Profile 15 Profile 16
f 13 -0.845 -0.744 -0.843 -0.765
f 21 0.535 0.472 0.496 0.453
f 32 0.816 0.714 0.749 0.673
f 41 0.556 0.492 0.647 0.643
f 53 0.492 0.439 0.497 0.443
f 54 0.201 0.167 0.196 0.164
f 64 0.916 0.816 1 1
Residual 0.0052 0.0041 0.0042 0.0057
  1. We solved a total of 100 problems, each corresponding to a different replication, generated randomly see Additional file 1: Table S1). The table shows the 16 cases for which the residual error is low.