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SUMMARY:Jiajun Zhang/张家军 (SYSU)
DTSTART:20201227T083000Z
DTEND:20201227T091500Z
DTSTAMP:20260423T024027Z
UID:iccm2020/17
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/iccm2020/17/
 ">Modelling and analysis of non-Markovian biochemical reaction networks</a
 >\nby Jiajun Zhang/张家军 (SYSU) as part of ICCM 2020\n\n\nAbstract\nMo
 deling intracellular processes has long relied on the Markovian assumption
 . However\, as soon as a reactant interacts with its environment\, molecul
 ar memory definitely exists and its effects cannot be neglected. Since the
  Markov theory cannot translate directly to modeling and analysis of non-M
 arkovian processes\, this leads to many significant challenges. We develop
  a formulation\, namely the stationary generalized chemical-master equatio
 n\, to model intracellular processes with molecular memory. This formulati
 on converts a non-Markovian question to a Markovian one while keeping the 
 stationary probabilistic behavior unchanged. Both a stationary generalized
  Fokker–Planck equation and a generalized linear noise approximation are
  further developed for the fast evaluation of fluctuations. These formulat
 ions can have broad applications and may help us discover new biological k
 nowledge.\n
LOCATION:https://researchseminars.org/talk/iccm2020/17/
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