Stochastic simulation of large biochemical systems by approximate Gillespie algorithm

Purutçuoğlu Gazi, Vilda
In recent years the fast innovations for the development of new methods and algorithms in system biology enable the biologists to analyze and interpret the complex biochemical structures. One of the speedy development has been seen in mathematical methods for generating these complex systems on the computer. These techniques help the researcher to ask biologically interesting questions and test their expectations before starting their biological experiments. There are a number of methods which can approximately simulate the biochemical systems in a computationally efficient way. In this study we present two applications of a recently developed simulation technique, called the approximate Gillespie, for approximately producing large systems with realistic complexity. We evaluate the performance of the new algorithm by comparing its simulation results with the ones generated from the well-known exact simulation technique, namely the Gillespie method.