In the mathematical modeling of biochemical reactions, a convenient standard approach is
to use ordinary differential equations (ODEs) that follow the law of mass action. However …

We obtain large deviation results for a two time-scale model of jump-diffusion processes.
The processes on the two time scales are fully inter-dependent, the slow process has small …

The last decade has witnessed a surge of theoretical and computational models to describe
the dynamics of complex gene regulatory networks, and how these interactions can give rise …

We investigate a broad family of stochastically modeled reaction networks by looking at their
stationary distributions. Most known results on stationary distributions assume weak …

We investigate the influence of intrinsic noise on stable states of a one-dimensional
dynamical system that shows in its deterministic version a saddle-node bifurcation between …

We consider a general class of autocatalytic reactions, which has been shown to display
stochastic switching behaviour (discreteness-induced transitions (DITs)) in some parameter …

The Togashi Kaneko model (TK model), introduced by Togashi and Kaneko in 2001, is a
simple stochastic reaction network that displays discreteness-induced transitions between …

We propose a novel measure valued process which models the behaviour of chemical
reaction networks in spatially heterogeneous systems. It models reaction dynamics between …

We investigate the statistics of the time taken for a system driven by recruitment to reach
fixation. Our model describes a series of experiments where a population is confronted with …

Biochemical reactions involved in complex cellular mechanisms are driven by inherently
stochastic molecular interactions. Although the intrinsic noise is often negligible in the …