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- W2971362506 abstract "Extrinsic noise-induced transitions have been largely investigated in a variety of chemical and physical systems. The key properties that make these systems mathematically tractable is that the noise appears linearly in the dynamical equations and it is assumed Gaussian and white. Here we consider the simplest unit of gene regulation, the repressed gene, which is instead characterized by nonlinear dependencies on external parameters, leading to corresponding nonlinear extrinsic noise. We adopt a general methodology to address this nonlinearity based on assuming that the fluctuations exhibit a finite and large correlation time. We also relax the Gaussian assumption, and consider the more biologically relevant log-normal noise. We find that in contrast to Gaussian noise, log-normal noise leads to noise-induced transitions, with the system becoming bimodal. We emphasize that no feedback loops are present in the system, and therefore our findings identify a novel class of noise-induced transitions, based on both features of noise nonlinearity and boundedness." @default.
- W2971362506 created "2019-09-12" @default.
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- W2971362506 date "2019-09-07" @default.
- W2971362506 modified "2023-09-27" @default.
- W2971362506 title "Bimodality without feedback: Noise-induced transitions in the repressed gene with extrinsic log-normal noise" @default.
- W2971362506 hasPublicationYear "2019" @default.
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