Kauffman网络中寻找吸引子方法的研究

Research of Finding Attractors in Kauffman Networks

Kauffman网络是基因调控网络的抽象模型,其统计特性与生物细胞的演化特征相匹配,所以用来模拟和分析生物系统的演化过程以及特定行为机制。由于Kauffman网络状态空间中吸引子对应于不同类型的细胞,其吸引子特性在一定程度上能够反映相应的生物系统功能,所以本文通过研究Kauffman网络的拓扑结构,结合SAT方法,从而确定了网络中吸引子的数量和长度,提高了在Kauffman网络中寻找吸引子算法的时空效率。

A Kauffman network is an abstract model of generic regulatory networks and the statistical characteristics of the model match the evolution of biological cells. So, a Kauffman network is used to simulate and analyze the evolution of biological systems as well as specific behavioral mechanisms. As attractors corresponding to different types of cells in the state space of a Kauffman network, characteristics of attractors reflect the corresponding function of biological systems to some extent. In this paper, the number and length of attractors is determined by studying the topology of the network with SAT methods and time and space efficiency of finding attractors is improved in Kauffman networks.