基于半张力积的概括异步布尔网络的长期行为估计,具有时间延迟
Guowei Li1, Chao Luo2, Shuang Zhou3
1College of Computer Science and Technology, Taiyuan University of Technology, Jinzhong 030600, China.
Chaos (Woodbury, N.Y.)
|July 28, 2025
概括
本研究分析了具有时间延迟的异步布尔网络的长期动态. 它建立了使用增强系统方法预测网络行为的条件,包括吸引器及其盆地.
科学领域:
- 系统生物学 系统生物学
- 计算生物学 计算生物学
- 网络动态 网络动态
背景情况:
- 布尔网络是基因调节网络的模型.
- 时间延迟和异步更新对于生物现实主义至关重要.
- 了解长期行为 (吸引力和盆地) 是预测系统稳定性和功能的关键.
研究的目的:
- 开发方法来估计具有时间延迟的通用异步布尔网络的长期行为.
- 描述吸引子及其在这些网络中的盆地的进化趋势.
- 为识别延迟固定点和限制周期提供必要和足够的条件.
主要方法:
- 将网络动态重新映射到使用代数状态空间表示的同等增强系统中.
- 为增强系统构建一个过渡表.
- 定义和识别基于增强系统和过渡表的延迟固定点和延迟极限周期.
- 分析状态过渡图和盆地重叠.
主要成果:
- 建立了延迟固定点和延迟极限周期存在的必要和充分条件.
- 开发了用于寻找这些延迟状态的吸引力盆地的方法.
- 提供了消除不同盆地之间重叠的条件.
- 通过使用大肠杆菌 (E. coli) 中的lac operon模型演示了这种方法.
结论:
- 提出的代数状态空间方法有效地描述了具有时间延迟的异步布尔网络的长期行为.
- 这些发现为分析复杂的生物调节系统提供了强大的框架.
- 该方法提供了对吸引力动态和盆地结构的洞察,这些结构对于理解系统稳定性和进化趋势至关重要.
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