title: Detecting small attractors of large Boolean networks by function-reduction-based strategy.
abstract: Boolean networks (BNs) are widely used to model gene regulatory networks and to design therapeutic intervention strategies to affect the long-term behaviour of systems. A central aim of Boolean-network analysis is to find attractors that correspond to various cellular states, such as cell types or the stage of cell differentiation. This problem is NP-hard and various algorithms have been used to tackle it with considerable success. The idea is that a singleton attractor corresponds to n consistent subsequences in the truth table. To find these subsequences, the authors gradually reduce the entire truth table of Boolean functions by extending a partial gene activity profile (GAP). Not only does this process delete inconsistent subsequences in truth tables, it also directly determines values for some nodes not extended, which means it can abandon the partial GAPs that cannot lead to an attractor as early as possible. The results of simulation show that the proposed algorithm can detect small attractors with length p = 4 in BNs of up to 200 nodes with average indegree K = 2.
authors.affiliation: Department of Physics and Electronic information engineering, Wenzhou University, Wenzhou 325035, Zhejiang, People's Republic of China.
authors.forename: Qiben
authors.initials: Q
authors.lastname: Zheng
authors.affiliation: Department of Physics and Electronic information engineering, Wenzhou University, Wenzhou 325035, Zhejiang, People's Republic of China.
authors.forename: Liangzhong
authors.initials: L
authors.lastname: Shen
authors.affiliation: School of Computer Science and Technology, Northwestern Polytechnical University, Xi'an 710072, People's Republic of China.
authors.forename: Xuequn
authors.initials: X
authors.lastname: Shang
authors.affiliation: Department of Physics and Electronic information engineering, Wenzhou University, Wenzhou 325035, Zhejiang, People's Republic of China. wbliu6910@126.com.
authors.forename: Wenbin
authors.initials: W
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D005786:Gene Expression Regulation / Q000502:physiology*; D006801:Humans; D016015:Logistic Models; D008954:Models, Biological; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology; D013269:Stochastic Processes
chemical_list: D020543:Proteome