FFCA: a feasibility-based method for flux coupling analysis of metabolic networks.
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ABSTRACT: Background
Flux coupling analysis (FCA) is a useful method for finding dependencies between fluxes of a metabolic network at steady-state. FCA classifies reactions into subsets (called coupled reaction sets) in which activity of one reaction implies activity of another reaction. Several approaches for FCA have been proposed in the literature.Results
We introduce a new FCA algorithm, FFCA (Feasibility-based Flux Coupling Analysis), which is based on checking the feasibility of a system of linear inequalities. We show on a set of benchmarks that for genome-scale networks FFCA is faster than other existing FCA methods.Conclusions
We present FFCA as a new method for flux coupling analysis and prove it to be faster than existing approaches. A corresponding software tool is freely available for non-commercial use at http://www.bioinformatics.org/ffca/.
SUBMITTER: David L
PROVIDER: S-EPMC3144024 | biostudies-literature | 2011 Jun
REPOSITORIES: biostudies-literature
Publications
FFCA: a feasibility-based method for flux coupling analysis of metabolic networks.
David Laszlo L Marashi Sayed-Amir SA Larhlimi Abdelhalim A Mieth Bettina B Bockmayr Alexander A
BMC bioinformatics 20110615
<h4>Background</h4>Flux coupling analysis (FCA) is a useful method for finding dependencies between fluxes of a metabolic network at steady-state. FCA classifies reactions into subsets (called coupled reaction sets) in which activity of one reaction implies activity of another reaction. Several approaches for FCA have been proposed in the literature.<h4>Results</h4>We introduce a new FCA algorithm, FFCA (Feasibility-based Flux Coupling Analysis), which is based on checking the feasibility of a s ...[more]
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