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Title: Discrimination of singleton and periodic attractors in Boolean networks
Authors: Cheng, Xiaoqing
Tamura, Takeyuki  kyouindb  KAKEN_id
Ching, Wai-Ki
Akutsu, Tatsuya  kyouindb  KAKEN_id
Author's alias: 田村, 武幸
阿久津, 達也
Keywords: Boolean networks
Boolean logic
Attractors
Observability
Discrimination
Biomarkers
Issue Date: Oct-2017
Publisher: Elsevier BV
Journal title: Automatica
Volume: 84
Start page: 205
End page: 213
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.
Rights: © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
The full-text file will be made open to the public on 01 October 2019 in accordance with publisher's 'Terms and Conditions for Self-Archiving'
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
URI: http://hdl.handle.net/2433/235515
DOI(Published Version): 10.1016/j.automatica.2017.07.012
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