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人工智能时代的中药网络药理学

Network pharmacology for traditional Chinese medicine in era of artificial intelligence.

作者信息

Zhao Weibo, Wang Boyang, Li Shao

机构信息

Institute for TCM-X, Department of Automation, Tsinghua University, 100084 Beijing, China.

出版信息

Chin Herb Med. 2024 Sep 3;16(4):558-560. doi: 10.1016/j.chmed.2024.08.004. eCollection 2024 Oct.

Abstract

Traditional Chinese Medicine Network Pharmacology (TCM-NP) is an interdisciplinary discipline that integrates information science, systems biology, network science and pharmacology, providing a systematic research methodology for TCM studies. With the development of artificial intelligence (AI) and multi-omics technologies, TCM-NP has entered a new era and can incorporate multimodal and high-dimensional data in the context of big data to enhance both theoretical foundations and technical capabilities. Despite its advancement, TCM-NP still faces challenges, particularly in ensuring the quality of data and research, as well as achieving more profound scientific discoveries. The field needs further innovation to obtain more precise and biomedically meaningful results. Overall research progress in TCM-NP depends on developing more accurate algorithms together with utilizing higher-quality and larger-scale data. This paper gives a perspective on the trends and characteristics of TCM-NP development and application in the era of AI.

摘要

中医网络药理学(TCM-NP)是一门融合信息科学、系统生物学、网络科学和药理学的交叉学科,为中医研究提供了一种系统的研究方法。随着人工智能(AI)和多组学技术的发展,中医网络药理学进入了一个新时代,能够在大数据背景下整合多模态和高维数据,以加强理论基础和技术能力。尽管取得了进展,但中医网络药理学仍面临挑战,特别是在确保数据和研究质量以及实现更深入的科学发现方面。该领域需要进一步创新,以获得更精确且具有生物医学意义的结果。中医网络药理学的整体研究进展取决于开发更精确的算法以及利用更高质量和更大规模的数据。本文对人工智能时代中医网络药理学的发展趋势和特点进行了展望。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e06e/11589279/d973925b4169/gr1.jpg

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