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使用基于个体的数学建模来了解更多关于宿主内抗生素耐药性的信息

Aminat Yetunde Saula¹, Christopher Rowlatt¹, Ruth Bowness²

¹Department of Mathematical Sciences, University of Bath, Bath, UK.

Methods in molecular biology (Clifton, N.J.)

|July 1, 2024

概括

基于个体的模型 (IBM) 模拟离散的代理和它们的相互作用,以理解复杂的系统行为. 这些基于代理的模型 (ABM) 可以有效地揭示集体模式和测试假设.

科学领域:

计算生物学计算生物学
系统生物学系统生物学
生态建模生态建模

背景情况:

复杂的系统需要简化模型进行分析.
基于个体的模型 (IBM),也称为基于代理的模型 (ABM),提供了一种方法来代表系统元素作为离散的代理.
这些代理具有独特的属性,并在基于预定义规则的空间环境中相互作用.

研究的目的:

在复杂系统模拟中解释基于个体模型 (IBM) 的原理和应用.
要突出 IBM/ABM 如何促进对代理-代理和代理-环境相互作用的理解.
证明IBM在建模随机事件和测试假设中的实用性.

主要方法:

模拟具有独特属性和行为规则的个体代理.
定义代理互动的空间环境.
通过概率分布将随机性纳入.
追踪个人代理行为和集体结果.

主要成果:

IBM有效地捕捉了代理级别的行为及其新兴的集体行为.
这些模型允许分析直接和间接的因果关系.
复杂的现象,包括像突变这样的罕见事件,可以准确地建模.

结论:

基于个体的模型为剖析复杂系统提供了一个强大的框架.
通过专注于单个代理互动,ABM可以对系统动态进行细致的理解.
这些模型促进了各种科学领域的新见解和假设测试.

关键词:

基于代理人的建模.抗生素耐药性抗生素耐药性不同方程的微分方程.数学建模的数学建模预测预测预测

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