准平衡状态和生物进化中的阶段过渡
Artem Romanenko1, Vitaly Vanchurin1,2
1Artificial Neural Computing, Weston, FL 33332, USA.
Entropy (Basel, Switzerland)
|March 28, 2024
概括
这项研究引入了一种使用香农 (S) 和哈明距离 (H) 的生物系统进化新模型. 这些发现揭示了系统如何在稳定状态之间过渡,提供了潜在的早期流行病预警能力.
科学领域:
- 进化的动力学.
- 复杂系统理论 复杂系统理论
- 生物信息学是一种生物信息学.
背景情况:
- 生物系统表现出复杂的进化动态.
- 了解稳定状态之间的过渡对于预测系统行为至关重要.
- 以前的模型可能无法完全捕捉宏观的进化转变.
研究的目的:
- 开发一个关于进化动态的宏观描述.
- 调查香农 (S) 和平均哈明距离 (H) 之间的关系.
- 探索这个框架作为流行病早期预警系统的潜力.
主要方法:
- 按照总的香农 (S) 和平均哈明距离 (H) 的时间动态.
- 分析S和H之间的相关性,以确定准平衡状态.
- 来自英国的SARS-CoV-2基因组数据的统计分析 (2020年3月 - 2023年12月).
主要成果:
- 生物系统可以在具有强烈S-H相关性特征的准平衡状态中持续存在.
- 准平衡状态之间的相变涉及热力学参数的不连续变化.
- 对SARS-CoV-2数据的分析表明了该模型的实际应用.
结论:
- 开发的宏观描述提供了对生物系统进化和相位过渡的洞察.
- 该框架为理解系统稳定性和变化提供了理论基础.
- 该模型显示,作为流行病等新兴传染病的早期预警系统,该模型具有前景.
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