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Table 1 Parameter estimations of the branched pathway model using noise-free data

From: Incremental parameter estimation of kinetic metabolic network models

  Simultaneous method Incremental method
  min Φ C b min Φ S C min ΦC min ΦS
CPU time (sec) a 56.00 h 620.81 ± 64.30 95.95 ± 11.09 1.56 ± 0.19
eSSM GO iterations 323 4390 ± 391 14 ± 4 10 ± 2
Parameter error (%) 49.10 36.91% ± 1.09 21.56% ± 7.57 × 10-2 36.85% ± 6.48 × 10-3
Φ C d 4.54 × 10 -3 6.54 × 10-3 ± 5.20 × 10-5 4.03 × 10-3  ± 6.22 × 10-8 6.00 × 10-3 ± 5.05 × 10-7
Φ S d 7.01 × 10-2 2.72 × 10-2 ± 1.09 × 10-5 3.92 × 10-2 ± 9.86 × 10-6 2.76 × 10-2 ± 4.46 × 10-10
  1. a. CPU time was based on a workstation with dual Intel Quad-Core 2.83 GHz processors.
  2. b. Only one out of five runs completed with a relative improvement of the objective function below 1% between iterations. The rest did not converge within the 5-day time limit after iterating for 583, 989, 777, and 661 times. The corresponding ΦC at termination were 4.85× 10-2, 1.39 × 10-2, 1.75 × 10-2 and 3.75 × 10-2, respectively.
  3. c. Mean value ± standard deviation out of five repeats.
  4. d. Root mean square error of model predictions, where the underlined value refers to the objective function of the minimization.