传统中医药中与系统药理学有关的数据库的多层次进步:对60年的回顾
Mengyue Fan1, Ching Jin2, Daping Li1
1Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
传统中医 (TCM) 研究使用计算方法来理解复杂的草药向相互作用. 本综述探讨了TCM数据库和未来的方向,包括深度学习,以加强药物发现.
科学领域:
- 计算药理学是一种计算药理学.
- 传统中医学的网络分析 (TCM)
- 生物信息学和数据库开发
背景情况:
- 传统医疗的治疗效果源于复杂的多组分,多目标相互作用.
- 计算方法,特别是网络分析,对于阐明TCM机制至关重要.
- 一个核心研究链 (公式-草药-组件-目标-表型-ZHENG) 帮助TCM数据组织.
研究的目的:
- 审查六个关键实体的TCM相关数据库的进展情况.
- 分析不同类型的数据库之间的共同点和差异.
- 确定TCM计算药理学的研究瓶和未来方向.
主要方法:
- 对涵盖配方,草药,成分,标,表型和ZHENG的数据库进行系统审查.
- 对数据库结构,数据类型和功能进行比较分析.
- 讨论新兴的计算技术,如深度学习和基础模型.
主要成果:
- 对于TCM实体的数据库已经进步,但趋向于同质性的趋势仍然存在.
- 在组织TCM数据沿配方-草药-成分-目标-表现型-ZHENG链路的显著进展.
- 识别TCM计算药理学研究瓶和创新机会.
结论:
- 计算技术的进步,如深度学习,有望彻底改变TCM研究.
- 解决数据库的一致性和瓶对于未来的进步至关重要.
- 新的计算方法对于更深入地了解TCM复杂系统至关重要.
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