标题： 连续时间中细胞的随机二进制建模作为生化反应方程的替代方法 显示英文标题

标题： Stochastic Binary Modeling of Cells in Continuous Time as an Alternative to Biochemical Reaction Equations

摘要： 我们开发了一种粗粒度公式，用于基于随机性和异质性而非生化反应来定量建模细胞的动态行为。 我们将每个反应视为一个连续时间随机过程，同时将每个生化量在单个细胞层面简化为二进制值。 该系统可以通过一组有限的常微分方程进行解析表示，这提供了每个分子状态的连续时间过程预测。 在本文中，我们介绍了我们的形式化方法，并通过几个示例进行了演示。 显示英文摘要

摘要： We have developed a coarse-grained formulation for modeling the dynamic behavior of cells quantitatively, based on stochasticity and heterogeneity, rather than on biochemical reactions. We treat each reaction as a continuous-time stochastic process, while reducing each biochemical quantity to a binary value at the level of individual cells. The system can be analytically represented by a finite set of ordinary linear differential equations, which provides a continuous time course prediction of each molecular state. In this letter, we introduce our formalism and demonstrate it with several examples.