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Estimating the solution space of Metabolic Networks
Mercoledý 11 Marzo 2009 ore 14.30 Andrea Pagnani - Fondazione ISI, Torino Cellular metabolism is one of the most investigated aspect of cell-wide biological interactions. While the topological nature of individual reactions and pathways in the network is quite well understood there is still a lack of comprehension regarding the global functional behavior of the system. To get some insight in this direction, in the last few years powerful theoretical methods such as extreme pathways calculation and flux-balance analysis have been introduced. 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. Using a technique derived from the fields of statistical physics and information theory we designed a stochastic algorithm to estimate the size of the affine space containing all possible steady-state flux distributions of metabolic networks. The algorithm, based on the Bethe approximation, allows the computation in polynomial time of the volume of a non full-dimensional convex polytope in high dimensions. We show results for toy models that compare very well with the results of exact algorithms, as well as for the E-Coli central metabolism that is intractable using standard techniques. The algorithm is used to test the effect of gene knock-outs on the size of the solution space of the E-coli central metabolism.
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