机制(生物学)
医学
中医药
中西医结合
系统药理学
数据集成
系统生物学
叙述性评论
数据科学
计算生物学
管理科学
计算机科学
药理学
替代医学
数据挖掘
重症监护医学
生物
药品
哲学
认识论
病理
经济
作者
Jiashuo Wu,Fangqing Zhang,Liu Zhuangzhuang,Weiyi Jin,Yue Shi
出处
期刊:PubMed
日期:2022-06-01
卷期号:42 (3): 479-486
被引量:88
标识
DOI:10.19852/j.cnki.jtcm.20220408.003
摘要
Traditional Chinese Medicine (TCM) has been extensively used as a mainstay for treating various pathologies. Combing the pharmacology and systems biology approaches, the network pharmacology (NP) approach was developed to predict the probable mechanism underlying the therapeutic effect of TCM. However, approaches solely based on NP cannot effectively elucidate the curative mechanism in a holistic and reliable manner due to limitations in NP-based methods and complexity of TCM components. Thus, integration strategies combining NP with other approaches are increasingly being used. Since the interdisciplinary research in TCM has received much attention in the advent of the big data era of which the NP-based integration strategy is broadly used, the strategy is clearly elaborated in the present review. We summarized several NP-based integration strategies and their applications in TCM studies, including multi-omics approach, gut microbiota study, chemical information analysis, data-mining, and network toxicology study.
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