Email updates

Keep up to date with the latest news and content from BMC Bioinformatics and BioMed Central.

Open Access Highly Accessed Methodology article

F2C2: a fast tool for the computation of flux coupling in genome-scale metabolic networks

Abdelhalim Larhlimi12*, Laszlo David345*, Joachim Selbig12 and Alexander Bockmayr34

Author Affiliations

1 Department of Bioinformatics, Institute for Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, D-14476 Potsdam, Germany

2 Max-Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam, Germany

3 FB Mathematik und Informatik, Freie Universität Berlin, Arnimallee 6, D-14195 Berlin, Germany

4 DFG-Research Center Matheon, Arnimallee 6, D-14195 Berlin, Germany

5 Berlin Mathematical School (BMS), Arnimallee 6, D-14195 Berlin, Germany

For all author emails, please log on.

BMC Bioinformatics 2012, 13:57  doi:10.1186/1471-2105-13-57

Published: 23 April 2012

Abstract

Background

Flux coupling analysis (FCA) has become a useful tool in the constraint-based analysis of genome-scale metabolic networks. FCA allows detecting dependencies between reaction fluxes of metabolic networks at steady-state. On the one hand, this can help in the curation of reconstructed metabolic networks by verifying whether the coupling between reactions is in agreement with the experimental findings. On the other hand, FCA can aid in defining intervention strategies to knock out target reactions.

Results

We present a new method F2C2 for FCA, which is orders of magnitude faster than previous approaches. As a consequence, FCA of genome-scale metabolic networks can now be performed in a routine manner.

Conclusions

We propose F2C2 as a fast tool for the computation of flux coupling in genome-scale metabolic networks. F2C2 is freely available for non-commercial use at https://sourceforge.net/projects/f2c2/files/ webcite.