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Article Dans Une Revue International Journal for Numerical Methods in Biomedical Engineering Année : 2012

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

Résumé

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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Dates et versions

hal-01061274 , version 1 (05-09-2014)

Identifiants

  • HAL Id : hal-01061274 , version 1
  • DOI : 10.1002/cnm.2476
  • ENSAM : http://hdl.handle.net/10985/8467

Citer

Amine Ammar, Elías Cueto, Francisco Chinesta. Reduction of the chemical master equation for gene regulatory networks using proper generalized decompositions. International Journal for Numerical Methods in Biomedical Engineering, 2012, 28 (9), pp.960-973. ⟨10.1002/cnm.2476⟩. ⟨hal-01061274⟩
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