Numerical Methods for the Chemical Master Equation

The dynamics of biochemical networks can be described by a Markov jump process on a high-dimensional state space, with the corresponding probability distribution being the solution of the Chemical Master Equation (CME). In this thesis, adaptive wavelet methods for the time-dependent and stationary CME, as well as for the approximation of committor probabilities are devised. The methods are illustrated on multi-dimensional models with metastable solutions and large state spaces.