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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.