人工智能时代的中药网络药理学

IF 4.7 4区 医学 Q1 CHEMISTRY, MEDICINAL Chinese Herbal Medicines Pub Date : 2024-10-01 DOI:10.1016/j.chmed.2024.08.004
Weibo Zhao, Boyang Wang, Shao Li
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引用次数: 0

摘要

摘要中药网络药理学(TCM-NP)是一门集信息科学、系统生物学、网络科学和药理学于一体的交叉学科,为中药研究提供了系统的研究方法。随着人工智能(AI)和多组学技术的发展,中医药网络药理学进入了一个新的时代,可以在大数据背景下纳入多模态和高维数据,提升理论基础和技术能力。尽管取得了进步,但中医药新药研究仍面临挑战,尤其是在确保数据和研究质量以及实现更深层次的科学发现方面。该领域需要进一步创新,以获得更精确、更有生物医学意义的结果。中医药基因组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。本文透视了人工智能时代中医药 NP 发展与应用的趋势和特点。
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Network pharmacology for traditional Chinese medicine in era of artificial intelligence

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.
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来源期刊
Chinese Herbal Medicines
Chinese Herbal Medicines CHEMISTRY, MEDICINAL-
CiteScore
4.40
自引率
5.30%
发文量
629
审稿时长
10 weeks
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