Robust Stabilizing Control of Perturbed Biological Networks via Coordinate Transformation and Algebraic Analysis

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This article investigates robust stabilizing control of biological systems modeled by Boolean networks (BNs). A population of BNs is considered where a majority of BNs have the same BN dynamics, but some BNs are inflicted by mutations damaging particular nodes, leading to perturbed dynamics that prohibit global stabilization to the desired attractor. The proposed control strategy consists of two steps. First, the nominal BN is transformed and curtailed into a sub-BN via a simple coordinate transformation and network reduction associated with the desired attractor. The feedback vertex set (FVS) control is then applied to the reduced BN to determine the control inputs for the nominal BN. Next, the control inputs derived in the first step and mutated nodes are applied to the nominal BN so as to identify residual dynamics of perturbed BNs, and additional control inputs are selected according to the canalization effect of each node. The overall control inputs are applied to the BN population, so that the nominal BN converges to the desired attractor and perturbed BNs to their own attractors that are the closest possible to the desired attractor. The performance of the proposed robust control scheme is validated through numerical experiments on random BNs and a complex biological network.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2024-03
Language
English
Article Type
Article
Citation

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, v.35, no.3, pp.3450 - 3463

ISSN
2162-237X
DOI
10.1109/TNNLS.2022.3192563
URI
http://hdl.handle.net/10203/322711
Appears in Collection
BiS-Journal Papers(저널논문)
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