Modeling of stochastic biological processes with non-polynomial propensities using non-central conditional moment equation

Abstract

Biological processes exhibiting stochastic fluctuations are mainly modeled using the Chemical Master Equation (CME). As a direct simulation of the CME is often computationally intractable, we recently introduced the Method of Conditional Moments (MCM). The MCM is a hybrid approach to approximate the statistics of the CME solution. In this work, we provide a more comprehensive formulation of the MCM by using non-central conditional moments instead of central conditional moments. The modified formulation allows for additional insight into the model structure and for extensions to higher-order reactions and non-polynomial propensity functions. The properties of the non-central MCM are analyzed using a model for the regulation of pili formation on the surface of bacteria, which possesses rational propensity functions.