The usual approach to simulating a biochemical system is to make a model which approximates that system, and then to solve the set of differential equations which comprise the model. There are many available algorithms which enable one to solve a set of differential equations numerically.
In many situations of biochemical interest, however, one is dealing with situations where there are only a few reactants of some species present. In these cases, the continuity assumption of the differential equation approach breaks down, and a numerical solution to the set of differential equations may lead to misleading results. An alternate approach is to perform a stochastic simulation of the system, whereby each reaction taking place is simulated, using Monte-Carlo methods. Following this approach is valid even when the reactant populations are very low, and indeed, one may see effects which are not apparent using the more traditional approach.
Very often, nevertheless, it is convenient to formulate the model in terms of differential equations, and it these which biochemists are often used to working with. The program described below takes a set of differential equations as input, extracts all necessary information, and performs a stochastic simulation of the system.