Table 1 |
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Different deletion strategies suggested by OptGene algorithm for improving succinate yield and Biomass Product Coupled Yield. |
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|
Objective function |
Number of deletions |
Suggested deletions1 |
Objective function value2 |
%Maximum Growth |
Unique solution?3 |
|
|
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|
Succinate yield |
5 |
SDH-complex, ZWF1, PDC6, U133, U221 |
0.39 |
14% |
Yes |
|
SDH-complex, ZWF1, PDC6, U133, U41 |
0.37 |
1% |
Yes |
||
|
4 |
SDH-complex, ZWF1, PDC6, AGP3 |
0.356 |
30% |
Yes |
|
|
3 |
SDH-complex, ZWF1, PFK2 |
0.211 |
4% |
Yes |
|
|
SDH-complex, SER3, THR1 |
0.074 |
76% |
Yes |
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|
Succinate Biomass Product Coupled Yield |
4 |
SDH-complex, ZWF1, PDC6, AGP3 |
29 |
30% |
Yes |
|
SDH-complex, SER3, THR1, U221 |
22 |
75% |
Yes |
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|
3 |
SDH-complex, SER3, THR1 |
16 |
76% |
Yes |
|
|
SDH-complex, ZWF1, GLT1 |
9.78 |
42% |
Yes |
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|
|
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|
1 Only few of the suggested strategies, with high objective function values are shown. OptGene found many strategies with different, but high objective function values. This tendency can be controlled by varying GA parameters. 2 Units are: Yield in gram (gram glucose)-1, Biomass Product Coupled Yield in milli-gram (gram-glucose.hour)-1 3 Uniqueness of the solution was verified by first optimizing for the biomass, and then minimizing and maximizing the succinate flux at fixed, optimal biomass value. |
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Patil et al. BMC Bioinformatics 2005 6:308 doi:10.1186/1471-2105-6-308 |
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