Table 1 |
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|
Performance of GJE versus SVD |
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|
Model |
Publ. |
Species |
Reactions |
Flux variables |
CPU time (s) |
εSVD ×10-12 |
Condition number |
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|
Orig. |
Open |
Dep. |
Indep. |
SVD |
GJE |
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|
|
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|
Example |
118 |
129 |
156 |
118 |
39 |
0.02 |
0.03 |
0.003 |
15 |
|
|
iPS189 |
[15] |
433 |
350 |
482 |
413 |
69 |
0.3 |
0.4 |
0.07 |
31000 |
|
iND750 |
[16] |
1177 |
1266 |
1561 |
1162 |
399 |
6.2 |
8.0 |
6.37 |
68000 |
|
AraGEM |
[17] |
1767 |
1625 |
2361 |
1720 |
641 |
19.7 |
34.2 |
12.65 |
3000 |
|
iAF1260 |
[18] |
1972 |
2382 |
2773 |
1960 |
813 |
30.5 |
34.3 |
1.43 |
2800 |
|
Recon 1 |
[10] |
3188 |
3742 |
4480 |
3169 |
1311 |
123.5 |
145.6 |
32.63 |
71000 |
|
|
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|
Kernel computation times for numerical SVD and symbolic GJE for the example yeast network given in Figure 3 and five genome-scale metabolic networks. All techniques are described in Methods. The condition number was calculated for Vindep from Equation (9). The inversion of Vindep is required to directly compare SVD results with the solution found from GJE. The difference between the results is given by ε SVD in Equation (11). |
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|
Schryer et al. BMC Systems Biology 2011 5:81 doi:10.1186/1752-0509-5-81 |
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