Table 2

Estimated patterns in distinguishing dynamic from static enzymes.

E. coli

1.000

0.750

0.500

0.250

0.100

0.075

0.050

0.025

0.010

Noise

Fitness (-)

7.83 × 10^-1

3.37

7.13 × 10^-1

3.30

6.42 × 10^-1

3.23

5.71 × 10^-1

3.16

5.06 × 10^-1

3.09

4.94 × 10^-1

3.08

4.82 × 10^-1

3.07

4.69 × 10^-1

3.05

4.59 × 10^-1

3.04

PGI

PFK

ALDO

TIS

GAPDH

PGK

PGluMu

ENO

PGM

G6PDH

PGDH

Ru5P

R5PI

TKa

TKb

S. cerevisiae

1000

0.750

0.500

0.250

0.100

0.075

0.050

0.025

0.010

Noise

Fitness (-)

3.35 × 10^-1

1.75 × 10¹

2.64 × 10^-1

1.75 × 10¹

1.94 × 10^-1

1.74 × 10¹

1.10 × 10^-1

1.73 × 10¹

5.42 × 10^-2

1.73 × 10¹

4.17 × 10^-2

1.73 × 10¹

4.17 × 10^-2

1.73 × 10¹

1.68 × 10^-2

1.72 × 10¹

8.02 × 10^-3

1.72 × 10¹

PGI

PFK

ALDO

TIS

GAPDH

PGK

PGluMu

ENO

PGM

G6PDH

PGDH

Ru5P

R5PI

TKa

TKb

w is the weighting coefficient in the fitness function (Eq. (5)), and the symbols D and S denote enzymes in the dynamic and static modules, respectively. The system boundary enzymes were omitted from the table because all system boundary enzymes were represented as dynamic enzymes.

Ishii et al. Theoretical Biology and Medical Modelling 2007 4:19 doi:10.1186/1742-4682-4-19