Title
Discrimination of singleton and periodic attractors in Boolean networks.
Abstract
Determining the minimum number of sensor nodes to observe the internal state of the whole system is important in analysis of complex networks. However, existing studies suggest that a large number of sensor nodes are needed to know the whole internal state. In this paper, we focus on identification of a small set of sensor nodes to discriminate statically and periodically steady states using the Boolean network model where steady states are often considered to correspond to cell types. In other words, we seek a minimum set of nodes to discriminate singleton and periodic attractors. We prove that one node is not necessarily enough but two nodes are always enough to discriminate two periodic attractors by using the Chinese remainder theorem. Based on this, we present an algorithm to determine the minimum number of nodes to discriminate all given attractors. We also present a much more efficient algorithm to discriminate singleton attractors. The results of computational experiments suggest that attractors in realistic Boolean networks can be discriminated by observing the states of only a small number of nodes.
Year
DOI
Venue
2017
10.1016/j.automatica.2017.07.012
Automatica
Keywords
Field
DocType
Boolean networks,Boolean logic,Attractors,Observability,Discrimination,Biomarkers
Boolean network,Attractor,Topology,Discrete mathematics,Mathematical optimization,Chinese remainder theorem,Complex network,Boolean algebra,Singleton,Small set,Periodic graph (geometry),Mathematics
Journal
Volume
Issue
ISSN
84
C
0005-1098
Citations 
PageRank 
References 
1
0.35
10
Authors
4
Name
Order
Citations
PageRank
Xiaoqing Cheng1123.26
Takeyuki Tamura221023.66
Wai-Ki Ching368378.66
Tatsuya Akutsu42169216.05