Combining bioinformatics, network pharmacology and artificial intelligence to predict the target genes of S-ketamine for treating major depressive disorder
S-ketamine may alleviate depression by targeting specific genes, including <i>TGM2</i>, <i>HSP90AB1</i> and <i>ADORA3</i>, as well as signalling pathways, including the gonadotropin-releasing hormone and relaxin signalling pathways.
Authors
- Kang Zhao (ORCID: https://orcid.org/0000-0002-5732-858X)
- zhou Xianjin
- Deng Shengqiong
- Shan Li (ORCID: https://orcid.org/0000-0002-9995-989X)
- Ying Wang (ORCID: https://orcid.org/0000-0003-4524-1812)
- Shen Fuyi (ORCID: https://orcid.org/0000-0001-5258-0287)
- Yang Ti
Institutions
- Hubei University of Medicine (CN)
- Second Military Medical University (CN)
- Ningxia Medical University (CN)
- Shanghai Pudong New Area Gongli Hospital (CN)
- Shanghai First Maternity and Infant Hospital (CN)
Publication Details
- Journal
- Journal of Psychopharmacology
- Published
- 2024-08-08
- DOI
- https://doi.org/10.1177/02698811241268884
- Citations
- 1
- Primary Topic
- Treatment of Major Depression
- Type
- article
- Field-Weighted Citation Impact
- 0.45
Funders
- Chinese Association of Integrative Medicine
- Shanghai Municipal Health Commission