Robust minimal strong reconstructibility problem of Boolean control networks

Xi Li, Yang Liu, Jungang Lou and Jianquan Lu

Applied Mathematics and Computation, 2023, vol. 458, issue C

Abstract: In this paper, the problem of robust minimal strong reconstructibility (RMSR) of Boolean control networks (BCNs) with multi-bit perturbations is studied by using graph theory. The problem takes the premise that BCNs are strongly reconstructible before function perturbation. We analyze the effect of the multi-bit perturbation on the strong reconstructibility of BCNs and present two valid criteria for the robust strong reconstructibility of BCNs. Then, to avoid the effect of function perturbation on the strong reconstructibility of BCNs, the problem of adding a minimal sensor set is considered, thereby making the BCNs robust minimal strong reconstructible after function perturbation. Finally, the results are applied to a biological example.

Keywords: Boolean control networks (BCN); Graph theory; Robust minimal strong reconstructibility (RMSR); Function perturbation (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:458:y:2023:i:c:s0096300323003788

DOI: 10.1016/j.amc.2023.128209

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