Abstract: Cellular behavior is stochastic, and studying stochastic in the cell can help to understand the organization, design and evolution of the cell. Establishment, identification and analysis of stochastic biochemical network models is an important research topic in the field of computational systems biology. At present, the standard Petri net model has become a powerful tool for biochemical network modeling and qualitative analysis. This paper attempts to apply stochastic Petri nets to modeling and analyzing biochemical network, it briefly describes the expansion of the stochastic Petri net theory to standard Petri nets, then by modeling and evolution simulating two classic examples（dimerization and actin）, it demonstrates new applications of stochastic Petri nets theory.

Key words: stochastic Petri nets, biochemical network, systems biology

摘要： 细胞的行为是随机性的，学习细胞中的随机性有助于理解细胞的组织，设计和进化。建立、确认和分析随机的生化网络模型是当前计算系统生物学领域的一个重要研究主题。当前，标准的Petri网模型已经成为生化网络模拟和定性分析的有力工具。尝试使用随机Petri网对生化网络进行建模与分析，简单描述了随机Petri网理论对标准Petri网的扩充，通过对二聚作用和肌动蛋白这两个典型例子的建模与演化模拟，介绍、论证了随机Petri网理论的新应用。

关键词: 随机Petri网, 生化网络, 系统生物学