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12个公开的中药数据库

数据库是中药网络药理学研究不可或缺的数据来源之一。目前已经建立了若干中药数据库，提供有关中药的各方面信息，包括疾病、方剂、草药或天然产物、生物活性成分和靶点。这些数据库成为中医药与现代生物医学之间的桥梁，在中药药理学研究中发挥了重要作用。这里列出12个公开的中药数据库。

点击以下数据库名称可以学习使用方法：

HIT 2.0

SymMap

TCMSID

LTM-TCM

ETCM

参考文献：

1. Ru J, Li P, Wang J, Zhou W, Li B, Huang C, Li P, Guo Z, Tao W, Yang Y et al:TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. Journal of cheminformatics 2014, 6:13.
2. Huang L, Xie D, Yu Y, Liu H, Shi Y, Shi T, Wen C: TCMID 2.0: a comprehensive resource for TCM. Nucleic Acids Res 2018, 46(D1):D1117-d1120.
3. Ji ZL, Zhou H, Wang JF, Han LY, Zheng CJ, Chen YZ: Traditional Chinese medicine information database. Journal of ethnopharmacology 2006, 103(3):501.
4. Fang S, Dong L, Liu L, Guo J, Zhao L, Zhang J, Bu D, Liu X, Huo P, Cao W et al: HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine. Nucleic Acids Res 2021,49(D1):D1197-d1206.
5. Yan D, Zheng G, Wang C, Chen Z, Mao T, Gao J, Yan Y, Chen X, Ji X, Yu J et al: HIT 2.0: an enhanced platform for Herbal Ingredients’ Targets. Nucleic Acids Res 2022, 50(D1):D1238-d1243.
6. Chen Q, Springer L, Gohlke BO, Goede A, Dunkel M, Abel R, Gallo K, Preissner S, Eckert A, Seshadri L et al: SuperTCM: A biocultural database combining biological pathways and historical linguistic data of Chinese Materia Medica for drug development. Biomedicine & Pharmacotherapy 2021, 144:112315.
7. Wu Y, Zhang F, Yang K, Fang S, Bu D, Li H, Sun L, Hu H, Gao K, Wang W et al: SymMap: an integrative database of traditional Chinese medicine enhanced by symptom mapping. Nucleic Acids Res 2019, 47(D1):D1110-d1117.
8. Zhang LX, Dong J, Wei H, Shi SH, Lu AP, Deng GM, Cao DS: TCMSID: a simplified integrated database for drug discovery from traditional chinese medicine. Journal of cheminformatics 2022,14(1):89.
9. Li X, Ren J, Zhang W, Zhang Z, Yu J, Wu J, Sun H, Zhou S, Yan K, Yan X et al: LTM-TCM: A comprehensive database for the linking of Traditional Chinese Medicine with modern medicine at molecular and phenotypic levels. Pharmacol Res 2022, 178:106185.
10. Tian S, Zhang J, Yuan S, Wang Q, Lv C, Wang J, Fang J, Fu L, Yang J, Zu X et al: Exploring pharmacological active ingredients of traditional Chinese medicine by pharmacotranscriptomic map in ITCM. Briefings in bioinformatics 2023, 24(2).
11. Zhang Y, Li X, Shi Y, Chen T, Xu Z, Wang P, Yu M, Chen W, Li B, Jing Z et al: ETCM v2.0: An update with comprehensive resource and rich annotations for traditional Chinese medicine. Acta Pharm Sin B 2023, 13(6):2559-2571.
12. Lv Q, Chen G, He H, Yang Z, Zhao L, Zhang K, Chen CY: TCMBank-the largest TCM database provides deep learning-based Chinese-Western medicine exclusion prediction. Signal transduction and targeted therapy 2023, 8(1):127.