Abstract
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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Acknowledgements
We would like to thank our anonymous reviewer, who contributed significantly to this manuscript, and especially for his tireless reviews of Kang et al. (2019). This material is based upon work supported by the National Science Foundation under Grant No. DMS-1616233.
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Enciso, G., Kim, J. Embracing Noise in Chemical Reaction Networks. Bull Math Biol 81, 1261–1267 (2019). https://doi.org/10.1007/s11538-019-00575-3
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DOI: https://doi.org/10.1007/s11538-019-00575-3