On Distribution and Enumeration of Attractors in Probabilistic Boolean Networks
In this paper, we study attractors in Probabilistic Boolean Networks (PBNs). We study the expected number of singleton attractors in a PBN and show that it is 1.5n if the number of Boolean functions assigned to each node is 2, where n is the number of nodes in a PBN. Then,we present algorithms for identifying singleton and small attractors and perform both theoretical and computational analyses on their average case time complexities. The results of computational experiments suggest that thcsc algorithms are much more efficient than the naive algorithm that examines all possible 2n states. We also show a simple and interesting relation between the distribution of attractors in a BN and the steady-state distribution in a corresponding variant of a PBN.
Probabilistic Boolean Network Attractor Algorithm
Morihiro Hayashida Takeyuki Tamura Tatsuya Akutsu Wai-Ki Ching
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji-city, Kyoto 6 Advanced Modelling and Applied Computing Laboratory, Department of Mathematics, The University of Ho
国际会议
The Second International Symposium(OSB08)(第二届国际优化及系统生物学学术会议)
云南丽江
英文
91-100
2008-10-31（万方平台首次上网日期，不代表论文的发表时间）