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Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets

机译:利用随机Petri网对分子生物学中的随机系统进行定量建模

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摘要

An integrated understanding of molecular and developmental biology must consider the large number of molecular species involved and the low concentrations of many species in vivo. Quantitative stochastic models of molecular interaction networks can be expressed as stochastic Petri nets (SPNs), a mathematical formalism developed in computer science. Existing software can be used to define molecular interaction networks as SPNs and solve such models for the probability distributions of molecular species. This approach allows biologists to focus on the content of models and their interpretation, rather than their implementation. The standardized format of SPNs also facilitates the replication, extension, and transfer of models between researchers. A simple chemical system is presented to demonstrate the link between stochastic models of molecular interactions and SPNs. The approach is illustrated with examples of models of genetic and biochemical phenomena where the UltraSAN package is used to present results from numerical analysis and the outcome of simulations.
机译:对分子生物学和发育生物学的综合理解必须考虑涉及的大量分子种类以及体内许多种类的低浓度。分子相互作用网络的定量随机模型可以表示为随机Petri网(SPN),这是计算机科学中发展起来的一种数学形式主义。现有软件可用于将分子相互作用网络定义为SPN,并针对分子种类的概率分布求解此类模型。这种方法使生物学家可以专注于模型的内容及其解释,而不是其实现。 SPN的标准化格式还有助于在研究人员之间复制,扩展和转移模型。提出了一个简单的化学系统来证明分子相互作用的随机模型和SPN之间的联系。用遗传和生化现象的模型示例说明了该方法,其中UltraSAN软件包用于显示数值分析和模拟结果。

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