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

In many applications, for example when computing statistics of fast subsystems in a
multiscale setting, we wish to find the stationary distributions of systems of continuous-time …

Biochemical processes typically involve many chemical species, some in abundance and
some in low molecule numbers. We first identify the rate constant limits under which the …

We consider stochastic descriptions of chemical reaction networks in which there are both
fast and slow reactions, and for which the time scales are widely separated. We develop a …

Biochemical reaction networks frequently consist of species evolving on multiple timescales.
Stochastic simulations of such networks are often computationally challenging and therefore …

In many applications, Bayesian inverse problems can give rise to probability distributions
which contain complexities due to the Hessian varying greatly across parameter space. This …

In this thesis we introduce a framework for parallel MCMC methods which we call parallel
adaptive importance sampling (PAIS). At each iteration we have an ensemble of particles …

In recent decades stochastic models have become an indispensable tool when analysing
quantitative biological data, which are often subject to noise, both from intrinsic and extrinsic …

Post-publication a small error was found in Example 1, a typo which also lead to comparing
the QSSA and constrained approximations to the wrong distribution. Below we represent this …