The Robustness of Balanced Boolean Networks
One of the characteristic features of genetic regulatory networks is their inherent robustness, that is, their ability to retain functionality in spite of the introduction of random errors. In this paper, we focus on the robustness of Balanced Boolean Networks (BBNs), which is a special kind of Boolean Network model of genetic regulatory networks. Our goal is to formalize and analyse the robustness of BBNs. Based on these results, applications using Boolean network model can be improved and optimized to be more robust.
We formalize BBNs and introduce a method to construct BBNs for 2-singleton attractors Boolean networks. The experiment results show that BBNs have a good performance on tolerating the single stuck-at faults on every edge. Our method improves the robustness of Boolean networks by at least 13% in average, and in some special case, up to 61%.
KeywordsBoolean Function Boolean Network Genetic Regulatory Network State Transition Graph Boolean Space
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