FFCA swMATH ID: 17351 Software Authors: David, L.; Marashi, S. A.; Larhlimi, A.; Mieth, B.; Bockmayr, A. Description: Ffca: a feasibility-based method for flux coupling analysis of metabolic networks. 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/. Homepage: http://www.bioinformatics.org/ffca/ Related Software: F2c2; efmtool; Metatool; fastGapFill; YANA; tFCA; BiGG Cited in: 4 Publications all top 5 Cited by 7 Authors 2 Bockmayr, Alexander 2 Marashi, Sayed-Amir 2 Tefagh, Mojtaba 1 Boyd, Stephen Poythress 1 David, Laszlo 1 Goldstein, Yaron 1 Reimers, Arne C. Cited in 3 Serials 2 Journal of Theoretical Biology 1 Journal of Mathematical Biology 1 Mathematical Biosciences Cited in 4 Fields 4 Biology and other natural sciences (92-XX) 2 Combinatorics (05-XX) 1 Calculus of variations and optimal control; optimization (49-XX) 1 Operations research, mathematical programming (90-XX) Citations by Year