Difference between revisions of "Flux Balance Constraint (analysis)"
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| − | + | === Flux balance Analysis === | |
| − | + | Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network. | |
| − | + | Metabolic reactions are represented as a stoichiometric matrix ''S''. The flux through all of the reactions in a network is represented by the vector ''v''. Flux Balance Analysis seeks to maximize or minimize an objective function ''Z = c<sup>T</sup>v'', which can be any linear combination of fluxes, where ''c'' is a vector of weights, indicating how much each reaction contributes to the objective function. FBA can thus be defined as the use of linear programming to solve the equation ''Sv = 0'' given a set of upper and lower bounds on ''v'' and a linear combination of fluxes as an objective function. | |
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| − | + | # Jeffrey D. Orth, Ines Thiele and Bernhard O. Palsson, "What is flux balance analysis?". Nature Biotechnology 28, 245–248 2010. | |
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[[Category:Analyses]] | [[Category:Analyses]] | ||
[[Category:DAE models (analyses group)]] | [[Category:DAE models (analyses group)]] | ||
[[Category:Autogenerated pages]] | [[Category:Autogenerated pages]] | ||
Revision as of 12:31, 12 April 2013
Flux balance Analysis
Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network.
Metabolic reactions are represented as a stoichiometric matrix S. The flux through all of the reactions in a network is represented by the vector v. Flux Balance Analysis seeks to maximize or minimize an objective function Z = cTv, which can be any linear combination of fluxes, where c is a vector of weights, indicating how much each reaction contributes to the objective function. FBA can thus be defined as the use of linear programming to solve the equation Sv = 0 given a set of upper and lower bounds on v and a linear combination of fluxes as an objective function.
- Jeffrey D. Orth, Ines Thiele and Bernhard O. Palsson, "What is flux balance analysis?". Nature Biotechnology 28, 245–248 2010.
