Drawert Brian, Hellander Stefan, Trogdon Michael, Yi Tau-Mu, Petzold Linda
Department of Computer Science, University of California-Santa Barbara, Santa Barbara, California 93106, USA.
Department of Mechanical Engineering, University of California-Santa Barbara, Santa Barbara, California 93106, USA.
J Chem Phys. 2016 Nov 14;145(18):184113. doi: 10.1063/1.4967338.
We have developed a method for modeling spatial stochastic biochemical reactions in complex, three-dimensional, and time-dependent domains using the reaction-diffusion master equation formalism. In particular, we look to address the fully coupled problems that arise in systems biology where the shape and mechanical properties of a cell are determined by the state of the biochemistry and vice versa. To validate our method and characterize the error involved, we compare our results for a carefully constructed test problem to those of a microscale implementation. We demonstrate the effectiveness of our method by simulating a model of polarization and shmoo formation during the mating of yeast. The method is generally applicable to problems in systems biology where biochemistry and mechanics are coupled, and spatial stochastic effects are critical.
我们已经开发出一种方法，可使用反应扩散主方程形式，对复杂的三维时变域中的空间随机生化反应进行建模。具体而言，我们希望解决系统生物学中出现的完全耦合问题，即细胞的形状和力学特性由生物化学状态决定，反之亦然。为了验证我们的方法并表征其中涉及的误差，我们将精心构建的测试问题的结果与微观尺度实现的结果进行了比较。我们通过模拟酵母交配过程中的极化和“shmoo”形成模型，证明了我们方法的有效性。该方法通常适用于系统生物学中生物化学与力学耦合且空间随机效应至关重要的问题。
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