Embracing Noise in Chemical Reaction Networks.

Authors:
German Enciso
German Enciso
University of California
Jinsu Kim
Jinsu Kim
Medical University of South Carolina
United States

Bull Math Biol 2019 May;81(5):1261-1267

Mathematics Department, University of California, Irvine, Irvine, CA, USA.

We provide a short review of stochastic modeling in chemical reaction networks for mathematical and quantitative biologists. We use as case studies two publications appearing in this issue of the Bulletin, on the modeling of quasi-steady-state approximations and cell polarity. Reasons for the relevance of stochastic modeling are described along with some common differences between stochastic and deterministic models.

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http://dx.doi.org/10.1007/s11538-019-00575-3DOI Listing
May 2019
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References

(Supplied by CrossRef)
Article in Bull Math Biol
DF Anderson et al.
Bull Math Biol 2010
Article in R Soc Interface
DF Anderson et al.
R Soc Interface 2014
Article in Bull Math Biophys
AF Bartholomay et al.
Bull Math Biophys 1958
Article in Bull Math Biophys
AF Bartholomay et al.
Bull Math Biophys 1959
Article in J Phys A
R Benzi et al.
J Phys A 1999
Article in J Chem Phys
M Delbrück et al.
J Chem Phys 1940
Article in Nature
MB Elowitz et al.
Nature 2000
Article in J Cell Sci
S Etienne-Manneville et al.
J Cell Sci 2004
Article in Arch Ration Mech Anal
M Feinberg et al.
Arch Ration Mech Anal 1972

PA Gagniuc et al.
2017
Article in Rev Mod Phys
L Gammaitoni et al.
Rev Mod Phys 1998

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