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

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons97261

Larhlimi,  A.
BioinformaticsCRG, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons97409

Selbig,  J.
BioinformaticsCRG, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Citation

Larhlimi, A., David, L., Selbig, J., & Bockmayr, A. (2012). F2C2: a fast tool for the computation of flux coupling in genome-scale metabolic networks. Bmc Bioinformatics, 13, 57. doi:10.1186/10.1186/1471-2105-13-57.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0014-1F3F-A
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/.