As we saw in the previous chapter, probability theory is a powerful framework for understanding random phenomena. For simple random systems, mathematical analysis alone can provide a complete description of all properties of interest. However, for the kinds of random systems that we are interested in (stochastic models of biochemical networks), mathematical analysis is not possible, and the systems are described as analytically intractable. However, this does not mean that it is not possible to understand such systems. With the aid of a computer, it is possible to simulate the time-evolution of the system dynamics. Stochastic simulation is concerned with the computer simulation of random (or ...
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