Kraus M, Lais P, Wolf B
Institut für Immunbiologie, Albert-Ludwigs-Universität Freiburg, FRG.
Biosystems. 1992;27(3):145-69. doi: 10.1016/0303-2647(92)90070-f.
In biology signal and information processing networks are widely known. Due to their inherent complexity and non-linear dynamics the time evolution of these systems can not be predicted by simple plausibility arguments. Fortunately, the power of modern computers allows the simulation of complex biological models. Therefore the problem becomes reduced to the question of how to develop a consistent mathematical model which comprises the essentials of the real biological system. As an interface between the phenomenological description and a computer simulation of the system the proposed method of Structured Biological Modelling (SBM) uses top-down levelled dataflow diagrams. They serve as a powerful tool for the analysis and the mathematical description of the system in terms of a stochastic formulation. The stochastic treatment, regarding the time evolution of the system as a stochastic process governed by a master equation, circumvents most difficulties arising from high dimensional and non-linear systems. As an application of SBM we develop a stochastic computer model of intracellular oscillatory Ca2+ waves in non-excitable cells. As demonstrated on this example, SBM can be used for the design of computer experiments which under certain conditions can be used as cheap and harmless counterparts to the usual time-consuming biological experiments.
在生物学中,信号和信息处理网络广为人知。由于其固有的复杂性和非线性动力学,这些系统的时间演化无法通过简单的合理性论证来预测。幸运的是,现代计算机的强大功能使得复杂生物模型的模拟成为可能。因此,问题就简化为如何开发一个包含真实生物系统要点的一致数学模型。作为系统现象学描述与计算机模拟之间的接口,所提出的结构化生物建模(SBM)方法使用自上而下分层的数据流图。它们作为一种强大的工具,用于根据随机公式对系统进行分析和数学描述。将系统的时间演化视为由主方程控制的随机过程的随机处理,规避了高维和非线性系统产生的大多数困难。作为SBM的一个应用,我们开发了一个非兴奋性细胞内振荡Ca2+波的随机计算机模型。正如这个例子所示,SBM可用于设计计算机实验,在某些条件下,这些实验可作为通常耗时的生物学实验的廉价且无害的替代方案。