多时间尺度生物系统混合建模与仿真工作流程。

IF 2 4区 生物学 Q2 BIOLOGY Biosystems Pub Date : 2024-11-21 DOI:10.1016/j.biosystems.2024.105365
Mostafa Herajy, Fei Liu, Monika Heiner
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引用次数: 0

摘要

随着实验室内生物实验的稳步发展,构建和模拟模型已成为了解和预测许多生物系统行为的普遍工具。然而,生物过程可能包含来自不同类型反应网络的成分,导致模型具有不同(如慢速和快速)的时标。混合模拟是有效执行多时间尺度模型的一种方法。在本文中,我们介绍了一种利用(彩色)混合 Petri 网构建更小、更复杂混合模型的方法和工作流程。所介绍的工作流程整合了生化反应网络混合模拟以及 Petri 网的算法和理念。我们还构建了多时标混合模型,然后展示了如何使用三种不同的高级混合仿真算法高效执行这些模型。
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A Workflow for the hybrid modelling and simulation of multi-timescale biological systems.

With the steady advance of in-silico biological experimentation, model construction and simulation becomes a ubiquitous tool to understand and predict the behaviour of many biological systems. However, biological processes may contain components from different types of reaction networks, resulting in models with different (e.g., slow and fast) timescales. Hybrid simulation is one approach which can be employed to efficiently execute multi-timescale models. In this paper, we present a methodology and workflow utilising (coloured) hybrid Petri nets to construct smaller and more complicated hybrid models. The presented workflow integrates algorithms and ideas from hybrid simulation of biochemical reaction networks as well as Petri nets. We also construct multi-timescale hybrid models and then show how these models can be efficiently executed using three different advanced hybrid simulation algorithms.

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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
期刊最新文献
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