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Exploration of the mechanism of traditional Chinese medicine by AI approach using unsupervised machine learning for cellular functional similarity of compounds in heterogeneous networks, XiaoErFuPi granules as an example.
Guo, Feifei; Tang, Xuan; Zhang, Wen; Wei, Junying; Tang, Shihuan; Wu, Hongwei; Yang, Hongjun.
Affiliation
  • Guo F; Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
  • Tang X; Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China; Tianjin University of Traditional Chinese Medicine, Tianjin, China.
  • Zhang W; Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China; Chengdu University of Traditional Chinese Medicine, Chengdu, China.
  • Wei J; Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
  • Tang S; Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China. Electronic address: shtang@icmm.ac.cn.
  • Wu H; Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China. Electronic address: hwwu@icmm.ac.cn.
  • Yang H; Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China; China Academy of Chinese Medical Sciences, Beijing, China. Electronic address: hjyang@icmm.ac.cn.
Pharmacol Res ; 160: 105077, 2020 10.
Article in En | MEDLINE | ID: mdl-32687952
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Drugs, Chinese Herbal / Systems Biology / Duodenum / Dyspepsia / Polypharmacology / Unsupervised Machine Learning / Medicine, Chinese Traditional Type of study: Diagnostic_studies Limits: Animals / Humans / Male Language: En Journal: Pharmacol Res Journal subject: FARMACOLOGIA Year: 2020 Document type: Article Affiliation country: China Country of publication: Países Bajos
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Drugs, Chinese Herbal / Systems Biology / Duodenum / Dyspepsia / Polypharmacology / Unsupervised Machine Learning / Medicine, Chinese Traditional Type of study: Diagnostic_studies Limits: Animals / Humans / Male Language: En Journal: Pharmacol Res Journal subject: FARMACOLOGIA Year: 2020 Document type: Article Affiliation country: China Country of publication: Países Bajos