I will present simulations of genetic switch systems with mutual
repression of two transcription factors. The simulations are done
using both deterministic methods, namely rate equations, and
stochastic methods including direct integration of the master
equation and Monte Carlo simulations. Numerous previous studies have
concluded that cooperative binding is a necessary condition for the
emergence of bistability in these systems. I will show that for a range of
biologically relevant conditions, a suitable combination of network
structure and stochastic effects gives rise to bistability even
without cooperative binding. I will then discuss the
difficulties one encounters in the attempt to simulate
large genetic networks using the master equation, namely that the
number of equations proliferates. I will then present a computational
methodology that enables to maintain the number of equations at
a manageable level.