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FASIMU: flexible software for flux-balance computation series in large metabolic networks

Andreas Hoppe1*, Sabrina Hoffmann1, Andreas Gerasch2, Christoph Gille1 and Hermann-Georg Holzhütter1

Author Affiliations

1 Institute of Biochemistry, University Medicine Charité Berlin, Seestr. 73, 13347 Berlin, Germany

2 Department of Parallel Computing, Wilhelm-Schickard Institute of Computer Science, Sand 13, 72076 Tübingen, Germany

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BMC Bioinformatics 2011, 12:28  doi:10.1186/1471-2105-12-28

Published: 22 January 2011



Flux-balance analysis based on linear optimization is widely used to compute metabolic fluxes in large metabolic networks and gains increasingly importance in network curation and structural analysis. Thus, a computational tool flexible enough to realize a wide variety of FBA algorithms and able to handle batch series of flux-balance optimizations is of great benefit.


We present FASIMU, a command line oriented software for the computation of flux distributions using a variety of the most common FBA algorithms, including the first available implementation of (i) weighted flux minimization, (ii) fitness maximization for partially inhibited enzymes, and (iii) of the concentration-based thermodynamic feasibility constraint. It allows batch computation with varying objectives and constraints suited for network pruning, leak analysis, flux-variability analysis, and systematic probing of metabolic objectives for network curation. Input and output supports SBML. FASIMU can work with free (lp_solve and GLPK) or commercial solvers (CPLEX, LINDO). A new plugin (faBiNA) for BiNA allows to conveniently visualize calculated flux distributions. The platform-independent program is an open-source project, freely available under GNU public license at webcite including manual, tutorial, and plugins.


We present a flux-balance optimization program whose main merits are the implementation of thermodynamics as a constraint, batch series of computations, free availability of sources, choice on various external solvers, and the flexibility on metabolic objectives and constraints.