传统医疗药物网络药理学:一个新的视角,将网络目标与人工智能和多模式多领域技术整合在一起
Ziyi Wang1, Tingyu Zhang1, Boyang Wang1
1Institute for TCM-X, MOE Key Laboratory of Bioinformatics, Bioinformatics Division, BNRIST/Department of Automation, Tsinghua University, Beijing 100084, China.
Chinese journal of natural medicines
|November 19, 2025
概括
网络药理学,使用网络目标,为传统中医药 (TCM) 研究提供了整体方法,克服了单一目标的局限性. 人工智能和多omics集成正在推进TCM.
科学领域:
- 综合医学和计算生物学.
- 探索中国传统医学 (TCM) 的机制.
背景情况:
- 传统中医 (TCM) 提供了独特的疾病预防和治疗好处.
- 减少主义的"单一药物,单一目标"模式与TCM的整体性质作斗争.
- 网络药理学提供了一个系统层面的方法来理解复杂的药物-疾病相互作用.
研究的目的:
- 审查TCM研究网络目标方法的进展.
- 在网络药理学中探索人工智能 (AI) 和多模式多态的整合.
- 突出这些综合方法在解码TCM原理,配方和毒性的应用.
主要方法:
- 网络药理学和网络目标理论作为核心框架.
- 计算和实验方法与人工智能相结合,用于预测疾病机制和药物向关系.
- 应用多模式多omics技术来分析TCM特征.
主要成果:
- 网络目标理论有效地弥合了TCM的整体原则和现代科学研究之间的差距.
- 人工智能和多组学显著提高了网络药理学的预测能力和分析深度.
- 这些综合方法在阐明TCM配方,综合征和毒性概况方面表现有前途.
结论:
- 网络目标理论,增强了AI和多omics,对于推进TCM研究至关重要.
- 新兴技术的未来整合将进一步完善TCM的网络目标方法.
- 这种协同作用有望在了解和创新TCM方面取得重大突破.
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