Koopman Theory for Boolean Networks

Networks of agents with logical states, namely Boolean networks, arise in various application domains including biology, computer networks, and social networks. The representation and control of Boolean networks have attracted much attention in recent years. In a parallel line of research, Koopman developed an operator view of nonlinear dynamical systems, which shows that, by making use of observable functions, every nonlinear dynamics can be represented as a (possibly infinite dimensional) linear system. In this paper, we present a Koopman theory for Boolean networks. We introduce algebraic operations for logical functions over semirings of binary numbers, defining a semimodule of Boolean functions. The classical Koopman operator and Koopman theory are then established for Boolean networks, where the key ingredient to a linear representation is shown to be Koopman invariance. Next, we establish a necessary and sufficient condition for shaping the closed-loop dynamics via feedback into any desired form for Boolean control networks under the Koopman representation, and we develop a feedback control synthesis algorithm to solve this feedback shaping problem. Finally, feedback shaping is applied to a real-world gene regulatory network, and it is demonstrated that the dynamics of such a network may be arbitrarily manipulated by means of feedback control.

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Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2025-08-14
DOI
https://doi.org/10.1109/tac.2025.3599022
Citations
2
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
1.61
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article

Koopman Theory for Boolean Networks

He Kong, Maria Elena Valcher, Hongsheng Qi, Guodong Shi
2 citations
IEEE Transactions on Automatic Control
Gene Regulatory Network Analysis
1.61
article

Koopman Theory for Boolean Networks

He Kong, Maria Elena Valcher, Hongsheng Qi, Guodong Shi
article en
2 citations

Abstract

Networks of agents with logical states, namely Boolean networks, arise in various application domains including biology, computer networks, and social networks. The representation and control of Boolean networks have attracted much attention in recent years. In a parallel line of research, Koopman developed an operator view of nonlinear dynamical systems, which shows that, by making use of observable functions, every nonlinear dynamics can be represented as a (possibly infinite dimensional) linear system. In this paper, we present a Koopman theory for Boolean networks. We introduce algebraic operations for logical functions over semirings of binary numbers, defining a semimodule of Boolean functions. The classical Koopman operator and Koopman theory are then established for Boolean networks, where the key ingredient to a linear representation is shown to be Koopman invariance. Next, we establish a necessary and sufficient condition for shaping the closed-loop dynamics via feedback into any desired form for Boolean control networks under the Koopman representation, and we develop a feedback control synthesis algorithm to solve this feedback shaping problem. Finally, feedback shaping is applied to a real-world gene regulatory network, and it is demonstrated that the dynamics of such a network may be arbitrarily manipulated by means of feedback control.

IEEE Transactions on Automatic ControlVol. 71(2)
University of Padua (IT), Chinese Academy of Sciences (CN), Southern University of Science and Technology (CN), Academy of Mathematics and Systems Science (CN), Australian Centre for Robotic Vision (AU)
Openalex Percentile: Top 15%
Gene Regulatory Network Analysis
1.61
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Koopman Theory for Boolean Networks — He Kong, Maria Elena Valcher, et al. · IEEE Transactions on Automatic Control (2025) | TGRS Research Map | TGRS