超越基因组:生物代码和能量约束的多尺度,基于代理的分类学
Cris Micheli1, Robert Prinz2, Pier Luigi Gentili3
1NeuroTechX Chapter, Berlin, 12161, Germany; Department of Management, Faculty of Management Sciences, Veritas University Abuja, Bwari Area Council, Federal Capital Territory, Nigeria.
Bio Systems
|October 6, 2025
概括
生命的信息分布在多个尺度上,挑战了以DNA为中心的观点. 这种计算方法整合了网络学和机器学习,以实现对生物系统的动态理解.
科学领域:
- * 系统生物学 系统生物学
- * 计算生物学 * 计算生物学
- * 理论生物学 理论生物学
背景情况:
- * 批判性地检查生物系统的组织原则.
- *挑战现代合成的重点是DNA,遗传网络和表观遗传学作为唯一的信息载体.
- * 提出生命的基本信息分布在多个尺度上.
研究的目的:
- *为理解生命的计算方法引入新兴规则.
- * 提出生物代码的初步分类法.
- * 通过稳定和探索动态来构建生命的等级结构.
主要方法:
- * 整合了来自网络学和机器学习的框架.
- * 应用诸如约束关闭和基于代理的建模等概念.
- * 分析生物代码的组成规则和层次关系.
主要成果:
- *识别生物信息分布在多个尺度上,而不仅仅是在DNA中.
- * 突出了细胞作为一个基本的网络智能代理.
- * 展示了复杂性中出现和自上而下的相互作用的作用.
- * 提出能量驱动的自构,适应和进化.
结论:
- * 跨尺度分布的信息是必要的,但不够的;环境相互作用至关重要.
- * 生物系统的功能是物理信息处理系统.
- *为分析和操纵复杂的生物系统提供了一个框架,对系统生物学和人工智能产生影响.
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