Tree-Based Search for Stochastic Simulation Algorithm

In systems biology, the cell behavior is governed by a series of biochemical reactions. The stochastic simulation algorithm (SSA), which was introduced by Gillespie, is a standard method to properly realize the dynamic and stochastic nature of such systems. In general, SSA follows a two-step approach: finding the next reaction firing, and updating the system accordingly. In this paper we apply the Huffman tree, an optimal tree for data compression, so to improve the search for the next reaction firing.