对于微生物组研究的随机通用洛特卡-沃尔特拉模型的弹性
Tuan A Phan1, Benjamin J Ridenhour2, Christopher H Remien2
1Institute for Modeling Collaboration and Innovation, University of Idaho, Moscow, ID 83844, USA.
Mathematical biosciences and engineering : MBE
|July 18, 2025
概括
环境噪音对微生物群体构成挑战. 我们介绍了一个随机通用的Lotka-Volterra (SgLV) 模型和弹性指标,以更好地从时间序列数据中预测微生物群稳定性.
科学领域:
- 微生物学 微生物学
- 生态建模 生态建模
- 计算生物学是一种计算生物学.
背景情况:
- 微生物群落由于环境随机性而表现出杂的时间序列数据.
- 传统的模型,如MAR和决定性的Lotka-Volterra,无法捕捉到这种环境波动.
- 准确的微生物组稳定性预测需要将随机性纳入数学模型.
研究的目的:
- 引入一个随机通用的Lotka-Volterra (SgLV) 系统来建模微生物社区动态.
- 根据SgLV模型开发一个计算弹性指标的理论框架.
- 提供评估微生物群弹性的一种实用方法.
主要方法:
- 开发了一个随机通用的Lotka-Volterra (SgLV) 模型.
- 创建了一个理论框架来计算四个不同的弹性措施.
- 利用模拟的微生物丰度数据集来演示计算程序.
主要成果:
- SgLV模型有效地描述了时间微生物社区的动态.
- 开发了四种新的弹性指标,捕捉了短期和长期的微生物群弹性.
- 拟议的方法为计算这些弹性指标提供了一个简单的程序.
结论:
- SgLV模型和相关的弹性指标为微生物组稳定性分析提供了强大的方法.
- 该框架解决了传统模型在环境随机性下预测微生物群行为的局限性.
- 该方法的简单性和实用性使其适用于各种微生物和生态系统.
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