Our research is focused on the exact or approximate solution of the chemical master equation describing biochemical systems, with a particular focus on gene regulatory networks. We are also interested in the approximate solution of the reaction-diffusion master equation and its extension to take into account the complex nature of the cytoplasm e.g. phenomena such as macromolecular crowding. Our main aim is to obtain closed-form solutions for the approximate distributions of molecule numbers (or of the moments) which can help us gain intuition about stochastic intracellular dynamics, in particular to understand how living cells have evolved to deal with inherent noise. More recently we have a burgeoning interest in developing efficient methods for the estimation of parameter values for gene regulatory networks from single cell and population snapshot data.