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SUMMARY:Reflected diffusions and (bio)chemical reaction networks
DTSTART;VALUE=DATE-TIME:20180712T054000Z
DTEND;VALUE=DATE-TIME:20180712T060000Z
DTSTAMP;VALUE=DATE-TIME:20200813T135936Z
UID:indico-contribution-388@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Ruth Williams (University of California\, San Diego)
\nContinuous-time Markov chain models are often used to describe the stoch
astic dynamics of networks of reacting chemical species\, especially in th
e growing field of systems biology. Discrete-event stochastic simulation o
f these models rapidly becomes computationally intensive. Consequently\, m
ore tractable diffusion approximations are commonly used in numerical comp
utation\, even for modest-sized networks. However\, existing approximation
s (e.g.\, linear noise and Langevin)\, do not respect the constraint that
chemical concentrations are never negative.\n\nIn this talk\, we propose
an approximation for such Markov chains\, via reflected diffusion processe
s\, that respects the fact that concentrations of chemical species are non
-negative. This fixes a difficulty with Langevin approximations that they
are frequently only valid until the boundary of the positive orthant is re
ached. Our approximation has the added advantage that it can be written do
wn immediately from the chemical reactions. Some numerical examples illust
rate the advantages of our approximation over direct simulation of the Mar
kov chain or use of the linear noise approximation.\n\nThis talk is based
on joint work with Saul Leite\, David Anderson and Des Higham.\n\nhttps://
conferences.maths.unsw.edu.au/event/2/contributions/388/
LOCATION:University of Sydney New Law School/--102
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/388/
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