Enciso German, Kim Jinsu
Mathematics Department, University of California, Irvine, Irvine, CA, USA.
Bull Math Biol. 2019 May;81(5):1261-1267. doi: 10.1007/s11538-019-00575-3.
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.
我们为数学和定量生物学领域的研究人员提供一份关于化学反应网络中随机建模的简要综述。我们将本期《简报》上发表的两篇论文作为案例研究，它们分别是关于准稳态近似建模和细胞极性建模的。文中阐述了随机建模的相关性理由以及随机模型与确定性模型之间的一些常见差异。
