OmniPath:用于多omics分析的综合知识库
Dénes Türei1, Jonathan Schaul1, Nicolàs Palacio-Escat1
1Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg 69120, Germany.
Nucleic acids research
|November 18, 2025
概括
OmniPath将来自168个资源的多样化分子知识集成到一个统一的数据库中. 本资源通过为机械模型提供可访问的先前知识来增强omics数据分析.
科学领域:
- 生物信息学是一种生物信息学.
- 系统生物学 系统生物学
- 计算生物学 计算生物学
背景情况:
- 奥米克斯数据分析在很大程度上依赖于先前的生物知识.
- 现有的知识资源往往是分散的,难以用于计算方法.
研究的目的:
- 开发OmniPath,一个综合多种分子相互作用和生物分子信息的综合数据库.
- 创建可访问的工具,包括OmniPath Explorer和客户端包,以利用这些知识进行omics分析.
主要方法:
- 来自168个不同资源的综合数据,包括文献策划的交互,预测和大规模数据库.
- 开发了OmniPath Explorer,具有用于交互式知识浏览的大型语言模型代理.
- 创建了Python和R/Bioconductor客户端包以及一个Cytoscape插件,用于与omics分析环境无集成.
主要成果:
- OmniPath巩固了因果蛋白-蛋白,基因调节,微RNA和酶-翻译后修饰相互作用.
- 数据库包括关于细胞-细胞通信,蛋白质复合体和生物分子功能,定位和结构的信息.
- OmniPath Explorer 和相关的软件包为omics研究提供了定制的先前知识检索.
结论:
- OmniPath提供了一个统一的和可访问的资源,用于先前的生物知识,对于OMIC数据解释至关重要.
- 开发的工具使集成的知识可用于机械和因果建模的应用,用于批量,单细胞和空间多omics数据分析.
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