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使用基于智能体的建模方法开发急性炎症反应协作性计算机模拟模型的概念。

Concepts for developing a collaborative in silico model of the acute inflammatory response using agent-based modeling.

作者信息

An Gary

机构信息

Department of Trauma, Cook County Hospital, Chicago, IL 60612, USA.

出版信息

J Crit Care. 2006 Mar;21(1):105-10; discussion 110-1. doi: 10.1016/j.jcrc.2005.11.012.

DOI:10.1016/j.jcrc.2005.11.012
PMID:16616634
Abstract

The complexity of the acute inflammatory response (AIR) is, by now, generally recognized. The primary manifestation of this property has been the difficulty in translating the information derived from reductionist, basic science research into effective clinical treatment regimens for sepsis. However, the recognition of the "complexity" of the AIR is not without its pitfalls. Despite its limitations, reductionism remains the primary means of obtaining scientific information. Furthermore, a functional shortcoming of use of the term complex has been to make it equivalent to "essentially unsolvable." Therefore, a mechanism is needed to integrate the apparatus of reductionist analysis into a complex synthetic methodology that overcomes the current limitations of both. Toward this end, I propose a structure for a class of collaborative, community-wide in silico models that use the framework of agent-based modeling. Agent-based modeling is a type of mathematical modeling that focuses on the behaviors of the components of complex systems and is well suited for translating the results of basic science experiments. I will also introduce a preliminary version of a syntactical "grammar" that can potentially be used to facilitate the transfer of basic science data into computer code. It is hoped that when a mature version of this framework is implemented, the resulting models will provide a functional, synthetic data base on the AIR that could be used for directing research, testing hypotheses, teaching and training, and drug discovery/testing.

摘要

急性炎症反应(AIR)的复杂性如今已得到普遍认可。这种特性的主要表现是,难以将源自还原论基础科学研究的信息转化为针对脓毒症的有效临床治疗方案。然而,认识到AIR的“复杂性”并非没有问题。尽管存在局限性,还原论仍然是获取科学信息的主要手段。此外,使用“复杂”一词在功能上的一个缺点是使其等同于“基本上无法解决”。因此,需要一种机制将还原论分析方法整合到一种复杂的综合方法中,以克服当前两者的局限性。为此,我提出了一类协作式、全社区范围的计算机模拟模型的结构,这些模型使用基于主体的建模框架。基于主体的建模是一种数学建模类型,专注于复杂系统组件的行为,非常适合转化基础科学实验的结果。我还将介绍一种句法“语法”的初步版本,它可能用于促进基础科学数据向计算机代码的转换。希望当这个框架的成熟版本实施时,生成的模型将提供一个关于AIR的功能性综合数据库,可用于指导研究、检验假设、教学与培训以及药物发现/测试。

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