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Reduction of the chemical master equation for gene regulatory networks using proper generalized decompositions

Article dans une revue avec comité de lecture
Author
ccAMMAR, Amine
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
ccCUETO, Elias
161327 Aragón Institute of Engineering Research [Zaragoza] [I3A]
ccCHINESTA SORIA, Francisco
10921 Institut de Recherche en Génie Civil et Mécanique [GeM]

URI
http://hdl.handle.net/10985/8467
DOI
10.1002/cnm.2476
Date
2012
Journal
International Journal for Numerical Methods in Biomedical Engineering

Abstract

The numerical solution of the chemical master equation (CME) governing gene regulatory networks and cell signaling processes remains a challenging task owing to its complexity, exponentially growing with the number of species involved. Although most of the existing techniques rely on the use of Monte Carlo-like techniques, we present here a new technique based on the approximation of the unknown variable (the probability of having a particular chemical state) in terms of a finite sum of separable functions. In this framework, the complexity of the CME grows only linearly with the number of state space dimensions. This technique generalizes the so-called Hartree approximation, by using terms as needed in the finite sums decomposition for ensuring convergence. But noteworthy, the ease of the approximation allows for an easy treatment of unknown parameters (as is frequently the case when modeling gene regulatory networks, for instance). These unknown parameters can be considered as new space dimensions. In this way, the proposed method provides solutions for any value of the unknown parameters (within some interval of arbitrary size) in one execution of the program.

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