Enhancing the Robustness of Random Boolean Networks by Epigenetic Regulation

Random Boolean Network (RBN) is a type of regulatory network in which the nodes have Boolean values representing their states.The robustness of RBNs against perturbations is a crucial characteristic, and there has been a growing interest in enhancing the network's robustness.In this study, a biologically inspired epigenetic regulation method is proposed to enhance the robustness of the RBNs.A frequency encoding method based on pulse counting is employed to encode the node states within a sliding time window, thereby improving the form of epigenetic regulation.To verify the performance of this method, an antifragility indicator is adopted to measure the robustness of RBNs and yeast cell networks at different scales.The experimental results demonstrate that the networks with epigenetic regulation exhibit excellent robustness, even in the presence of large-scale networks and severe perturbations.This approach provides a new perspective and idea for designing robust RBNs and discrete networks.

Publication Details

Journal
Cronfa (Swansea University)
Published
2025-01-01
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Enhancing the Robustness of Random Boolean Networks by Epigenetic Regulation

Cronfa (Swansea University)
Gene Regulatory Network Analysis
article

Enhancing the Robustness of Random Boolean Networks by Epigenetic Regulation

article en

Abstract

Random Boolean Network (RBN) is a type of regulatory network in which the nodes have Boolean values representing their states.The robustness of RBNs against perturbations is a crucial characteristic, and there has been a growing interest in enhancing the network's robustness.In this study, a biologically inspired epigenetic regulation method is proposed to enhance the robustness of the RBNs.A frequency encoding method based on pulse counting is employed to encode the node states within a sliding time window, thereby improving the form of epigenetic regulation.To verify the performance of this method, an antifragility indicator is adopted to measure the robustness of RBNs and yeast cell networks at different scales.The experimental results demonstrate that the networks with epigenetic regulation exhibit excellent robustness, even in the presence of large-scale networks and severe perturbations.This approach provides a new perspective and idea for designing robust RBNs and discrete networks.

Cronfa (Swansea University)
British Columbia Innovation Council, National Natural Science Foundation of China, Natural Science Foundation of Guangxi Province, Guangxi Normal University
Openalex Percentile: Top 51%
Gene Regulatory Network Analysis
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