Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2007-09-06
BMC Bioinformatics. 2008;9:240
Physics
Condensed Matter
Disordered Systems and Neural Networks
8 pages, 7 pdf figures
Scientific paper
In this work we propose a novel algorithmic strategy that allows for an efficient characterization of the whole set of stable fluxes compatible with the metabolic constraints. The algorithm, based on the well-known Bethe approximation, allows the computation in polynomial time of the volume of a non full-dimensional convex polytope in high dimensions. The result of our algorithm match closely the prediction of Monte Carlo based estimations of the flux distributions of the Red Blood Cell metabolic network but in incomparably shorter time. We also analyze the statistical properties of the average fluxes of the reactions in the E-Coli metabolic network and finally to test the effect of gene knock-outs on the size of the solution space of the E-Coli central metabolism.
Braunstein Alfredo
Mulet Roberto
Pagnani Andrea
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