用模块化单元动态模拟系统模拟扩散。

Q2 Medicine
Christoph Leberecht, Florian Heinke, Dirk Labudde
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引用次数: 4

摘要

各种各样的数学模型被用来描述和模拟生命科学中检验的众多自然过程。在本文中,我们提出了一个可扩展和可调节的自然系统模拟基础。该模型基于图中的邻域关系和元胞自动机中复杂的相互作用,利用递归关系在中观尺度上模拟变化。这种隐式定义允许对模型的各个方面进行操作,甚至在模拟过程中也是如此。值规则ω的定义有助于在时间步长期间积累变化。这些变化可能是由不同的物理、化学或生物现象引起的。可以将值规则组合到模块中,然后使用模块创建基线模型。通过实例,设计了化学物质扩散的数值规则,并对其适用性进行了论证。最后对解的稳定性和准确性进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulation of diffusion using a modular cell dynamic simulation system.

A variety of mathematical models is used to describe and simulate the multitude of natural processes examined in life sciences. In this paper we present a scalable and adjustable foundation for the simulation of natural systems. Based on neighborhood relations in graphs and the complex interactions in cellular automata, the model uses recurrence relations to simulate changes on a mesoscopic scale. This implicit definition allows for the manipulation of every aspect of the model even during simulation. The definition of value rules ω facilitates the accumulation of change during time steps. Those changes may result from different physical, chemical or biological phenomena. Value rules can be combined into modules, which in turn can be used to create baseline models. Exemplarily, a value rule for the diffusion of chemical substances was designed and its applicability is demonstrated. Finally, the stability and accuracy of the solutions is analyzed.

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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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