Non-Gaussian Noise Accelerates State Transitions in Bistable Biochemical Networks: A Stochastic Simulation Study

Elena Zancanaro, Margherita Bonan, Lin Wei

Abstract


This work investigates how non-Gaussian noise (e.g., Lévy fluctuations) drives state transitions in bistable biochemical networks. Using stochastic simulations (Gillespie algorithm), we show that heavy-tailed noise enhances transition rates between stable states compared to Gaussian noise. Our analysis reveals a statistical coupling between noise properties and network dynamics, offering new insights into controlling cellular decision-making processes.

Keywords


Non-Gaussian noise, bistable systems, stochastic switching, systems biology

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References


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DOI: http://dx.doi.org/10.52155/ijpsat.v52.1.7443

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