title: Construction and accuracy of partial differential equation approximations to the chemical master equation.
abstract: The mesoscopic description of chemical kinetics, the chemical master equation, can be exactly solved in only a few simple cases. The analytical intractability stems from the discrete character of the equation, and hence considerable effort has been invested in the development of Fokker-Planck equations, second-order partial differential equation approximations to the master equation. We here consider two different types of higher-order partial differential approximations, one derived from the system-size expansion and the other from the Kramers-Moyal expansion, and derive the accuracy of their predictions for chemical reactive networks composed of arbitrary numbers of unimolecular and bimolecular reactions. In particular, we show that the partial differential equation approximation of order Q from the Kramers-Moyal expansion leads to estimates of the mean number of molecules accurate to order Ω(-(2Q-3)/2), of the variance of the fluctuations in the number of molecules accurate to order Ω(-(2Q-5)/2), and of skewness accurate to order Ω(-(Q-2)). We also show that for large Q, the accuracy in the estimates can be matched only by a partial differential equation approximation from the system-size expansion of approximate order 2Q. Hence, we conclude that partial differential approximations based on the Kramers-Moyal expansion generally lead to considerably more accurate estimates in the mean, variance, and skewness than approximations of the same order derived from the system-size expansion.
authors.affiliation: School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.
authors.forename: Ramon
authors.initials: R
authors.lastname: Grima
mesh_terms: D000465:Algorithms; D001703:Biophysics / Q000379:methods*; D002627:Chemistry, Physical; D003198:Computer Simulation; D007700:Kinetics; D008956:Models, Chemical; D015233:Models, Statistical; D008968:Molecular Conformation; D011336:Probability; D015203:Reproducibility of Results; D013997:Time Factors