Cells use signaling networks consisting of multiple interacting proteins to respond to changes in their environment. In many situations, such as chemotaxis, spatial and temporal information must be transmitted through the network. Recent computational studies have emphasized the importance of cellular geometry in signal transduction, but have been limited in their ability to accurately represent complex cell morphologies. We present a finite volume method that addresses this problem. Our method uses Cartesian cut cells and is second order in space and time. We use our method to simulate several models of signaling systems in realistic cell morphologies obtained from live cell images and examine the effects of geometry on signal transduction.

中文翻译：

---

用于模拟任意几何形状中生化反应网络空间模型的切割单元法。

细胞使用由多种相互作用的蛋白质组成的信号网络来响应其环境的变化。在许多情况下，例如趋化性，空间和时间信息必须通过网络传输。最近的计算研究强调了细胞几何在信号转导中的重要性，但在准确表示复杂细胞形态的能力方面受到限制。我们提出了一种解决这个问题的有限体积方法。我们的方法使用笛卡尔切割单元，并且在空间和时间上是二阶的。我们使用我们的方法在从活细胞图像中获得的真实细胞形态中模拟信号系统的几种模型，并检查几何对信号转导的影响。