Identifying separated time scales in stochastic models of reaction networks
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If you have a question about this talk, please contact Sarah Lilienthal.
Joint with Newton Institue, Stochastic Processes in Communication Sciences Program.
For chemical reaction networks in biological cells, reaction rates and
chemical species numbers may vary over several orders of magnitude.
Combined, these large variations can lead to subnetworks operating on very
different time scales. Separation of time scales has been exploited in many
contexts as a basis for reducing the complexity of dynamic models, but the
interaction of the rate constants and the species numbers makes identifying
the appropriate time scales tricky at best. Some systematic approaches to
this identification will be discussed and illustrated by application to one
or more complex reaction network models.
This talk is part of the Optimization and Incentives Seminar series.
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