Regulatory gene networks contain generic modules like those involving
feedback loops, which are essential for the regulation of many biological
functions. We consider a class of self-regulated genes which are the building
blocks of many regulatory gene networks, and study the steady state
distributions of the associated Gillespie algorithm by providing efficient
numerical algorithms. We also study a regulatory gene network of interest in
synthetic biology and in gene therapy, using mean-field models with time
delays. Convergence of the related time-nonhomogeneous Markov chain is
established for a class of linear catalytic networks with feedback loop
