扩大生物信息学:从数据转向理论的范式转变
Zhang Zhang1,2,3
1National Genomics Data Center, China National Center for Bioinformation, Beijing 100101, China.
Fundamental research
|February 6, 2026
概括
生物信息学正在从数据分析扩展到理论发展,转变生物研究. 这种转变为理解复杂的生物系统和推进人工智能建模提供了一个整体的方法.
科学领域:
- 生物信息学和计算生物学
- 系统生物学 系统生物学
- 人工智能在生物学中的应用
背景情况:
- 生物数据的指数增长需要先进的分析方法.
- 当前生物信息学实践往往侧重于数据处理,而不是理论整合.
- 需要弥合生物数据和理论框架之间的差距.
研究的目的:
- 为扩大生物信息学从数据到理论提出一个愿景.
- 概述这一扩张如何推动生物研究的范式转变.
- 加强生物信息学作为一个学科的连贯性和身份.
主要方法:
- 概念框架发展 概念框架发展
- 关于生物信息学和理论生物学的文学综合.
- 对人工智能和实验设计潜在影响的分析.
主要成果:
- 拟议扩展生物信息学以将数据驱动的见解与理论框架相结合.
- 确定将生物数据转化为可操作的理论的途径.
- 演示如何以理论为中心的方法可以提高AI模型的可解释性和效率.
结论:
- 将生物信息学从数据扩展到理论是生物学范式转变的关键.
- 这种综合方法将促进对复杂生物系统的更全面的理解.
- 加强生物信息学的理论基础将推动人工智能驱动的生物发现.
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