Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.
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February 2015
Research Article|
February 10 2015
Controllability and observability of Boolean networks arising from biology
Rui Li;
Rui Li
1Key Laboratory of Systems and Control,
Institute of Systems Science
, Chinese Academy of Sciences, Beijing 100190, China
2State Key Laboratory for Turbulence and Complex Systems, College of Engineering,
Peking University
, Beijing 100871, China
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Meng Yang;
Meng Yang
3
China Ship Development and Design Center
, Wuhan 430064, China
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Tianguang Chu
Tianguang Chu
a)
2State Key Laboratory for Turbulence and Complex Systems, College of Engineering,
Peking University
, Beijing 100871, China
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a)
Author to whom correspondence should be addressed. Electronic mail: chutg@pku.edu.cn.
Chaos 25, 023104 (2015)
Article history
Received:
November 23 2014
Accepted:
January 24 2015
Citation
Rui Li, Meng Yang, Tianguang Chu; Controllability and observability of Boolean networks arising from biology. Chaos 1 February 2015; 25 (2): 023104. https://doi.org/10.1063/1.4907708
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