TY  - JOUR
A1  - David, Laszlo
A1  - Marashi, Sayed-Amir
A1  - Larhlimi, Abdelhalim
A1  - Mieth, Bettina
A1  - Bockmayr, Alexander
T1  - FFCA a feasibility-based method for flux coupling analysis of metabolic networks
JF  - BMC bioinformatics
N2  - 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/.
Y1  - 2011
U6  - https://doi.org/10.1186/1471-2105-12-236
SN  - 1471-2105
VL  - 12
IS  - 12
PB  - BioMed Central
CY  - London
ER  -