| Literature DB >> 18433192 |
Abstract
A quasi-Monte Carlo method for the simulation of discrete time Markov chains is applied to the simulation of biochemical reaction networks. The continuous process is formulated as a discrete chain subordinate to a Poisson process using the method of uniformization. It is shown that a substantial reduction of the number of trajectories that is required for an accurate estimation of the probability density functions (PDFs) can be achieved with this technique. The method is applied to the simulation of two model problems. Although the technique employed here does not address the typical stiffness of biochemical reaction networks, it is useful when computing the PDF by replication. The method can also be used in conjuncture with hybrid methods that reduce the stiffness.Mesh:
Year: 2008 PMID: 18433192 DOI: 10.1063/1.2897976
Source DB: PubMed Journal: J Chem Phys ISSN: 0021-9606 Impact factor: 3.488