AI时代的纵向生物大数据。

IF 7.7 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Molecular Systems Biology Pub Date : 2025-09-01 Epub Date: 2025-08-05 DOI:10.1038/s44320-025-00134-0
Adil Mardinoglu, Hasan Turkez, Minho Shong, Vishnuvardhan Pogunulu Srinivasulu, Jens Nielsen, Bernhard O Palsson, Leroy Hood, Mathias Uhlen
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引用次数: 0

摘要

生成纵向和多层大生物数据对于有效实施人工智能(AI)和系统生物学方法来表征健康和复杂疾病状态下的全身生物功能至关重要。生物大数据包括多组学、临床、可穿戴设备、影像数据,以及饮食、药物、毒素等环境因素信息。鉴于组学技术、人类代谢基因组学和计算能力的重大进步,一些多组学研究正在进行中。在这里,我们首先回顾了人工智能和系统生物学在整合和解释多组学数据方面的最新应用,强调了它们对创建数字双胞胎和发现新的生物标志物和药物靶点的贡献。接下来,我们回顾了全球范围内产生的多组学数据集,以揭示随着时间的推移,多个生物层信息之间的相互作用,从而增强了精准健康和医学。最后,我们解决了将大生物学数据纳入临床实践的需求,支持开发对人工智能驱动的医院至关重要的临床决策支持系统,并为基于人工智能和系统生物学的医疗保健模型奠定基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Longitudinal big biological data in the AI era.

Longitudinal big biological data in the AI era.

Longitudinal big biological data in the AI era.

Longitudinal big biological data in the AI era.

Generating longitudinal and multi-layered big biological data is crucial for effectively implementing artificial intelligence (AI) and systems biology approaches in characterising whole-body biological functions in health and complex disease states. Big biological data consists of multi-omics, clinical, wearable device, and imaging data, and information on diet, drugs, toxins, and other environmental factors. Given the significant advancements in omics technologies, human metabologenomics, and computational capabilities, several multi-omics studies are underway. Here, we first review the recent application of AI and systems biology in integrating and interpreting multi-omics data, highlighting their contributions to the creation of digital twins and the discovery of novel biomarkers and drug targets. Next, we review the multi-omics datasets generated worldwide to reveal interactions across multiple biological layers of information over time, which enhance precision health and medicine. Finally, we address the need to incorporate big biological data into clinical practice, supporting the development of a clinical decision support system essential for AI-driven hospitals and creating the foundation for an AI and systems biology-based healthcare model.

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来源期刊
Molecular Systems Biology
Molecular Systems Biology 生物-生化与分子生物学
CiteScore
18.50
自引率
1.00%
发文量
62
审稿时长
6-12 weeks
期刊介绍: Systems biology is a field that aims to understand complex biological systems by studying their components and how they interact. It is an integrative discipline that seeks to explain the properties and behavior of these systems. Molecular Systems Biology is a scholarly journal that publishes top-notch research in the areas of systems biology, synthetic biology, and systems medicine. It is an open access journal, meaning that its content is freely available to readers, and it is peer-reviewed to ensure the quality of the published work.
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