title: Algorithms for finding small attractors in Boolean networks.
abstract: A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in O(1.19(n)) time for K = 2, which is much faster than the naive O(2(n)) time algorithm, where n is the number of genes and K is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.
authors.affiliation: Advanced Modeling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong.
authors.forename: Shu-Qin
authors.initials: SQ
authors.lastname: Zhang
authors.forename: Morihiro
authors.initials: M
authors.lastname: Hayashida
authors.forename: Tatsuya
authors.initials: T
authors.lastname: Akutsu
authors.forename: Wai-Ki
authors.initials: WK
authors.lastname: Ching
authors.forename: Michael K
authors.initials: MK
authors.lastname: Ng