Stochastic fluctuations of molecule numbers are ubiquitous in biological systems. Important
examples include gene expression and enzymatic processes in living cells. Such systems …

Mathematical models are routinely calibrated to experimental data, with goals ranging from
building predictive models to quantifying parameters that cannot be measured. Whether or …

This practical introduction to stochastic reaction-diffusion modelling is based on courses
taught at the University of Oxford. The authors discuss the essence of mathematical methods …

Of all plastics, the most abundantly produced is polyethylene, most of which is destined for
landfills, ship** ports, and natural environments. The limited degradability and …

Abstract Models of chemical kinetics that incorporate both stochasticity and diffusion are an
increasingly common tool for studying biology. The variety of competing models is vast, but …

The noisy dynamics of chemical systems is commonly studied using either the chemical
master equation (CME) or the chemical Fokker-Planck equation (CFPE). The latter is a …

Both natural ecosystems and biochemical reaction networks involve populations of
heterogeneous agents whose cooperative and competitive interactions lead to a rich …

Computational biology is the science of develo** mathematical models and numerical
simulation techniques to understand biological and biochemical systems. Since the early …

We present a method that captures the fluctuations beyond mean field in chemical reactions
in the regime of small copy numbers and hence large fluctuations, using self-consistently …

Stochasticity plays a fundamental role in various biochemical processes, such as cell
regulatory networks and enzyme cascades. Isothermal, well-mixed systems can be …