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- W2912061779 abstract "In this paper, a class of stochastic hybrid systems comprising of multiple operation modes is studied. In each mode, the state evolves according to a linear stochastic differential equation. We allow for stochastic switching between operational modes with switching times controlled by an underlying renewal process such that the time spent in each mode is a random variable with an arbitrary given probability distribution. We present a novel method to derive exact analytical solutions for the statistical moments, and illustrate the applicability of the method on an example drawn from systems biology. More specifically, we study how random switching of a gene between transcriptionally active and inactive states drives stochastic variation in the level of the expressed protein. Our results show that while randomness in gene switching times has no effect on the mean protein level, it critically impacts the magnitude of fluctuations in the protein level. This effect is further amplified for proteins with high decay rate. We finally discuss how noise in protein levels can be used to infer the underlying gene expression mechanisms." @default.
- W2912061779 created "2019-02-21" @default.
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- W2912061779 date "2018-12-01" @default.
- W2912061779 modified "2023-09-23" @default.
- W2912061779 title "Exact statistical moments of multi-mode stochastic hybrid systems with renewal transitions" @default.
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- W2912061779 doi "https://doi.org/10.1109/cdc.2018.8619667" @default.
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