Bei Jing
Impact in
- Pharmacology top 5%
- Pharmacological Effects of Natural Compounds
- Neurology top 10%
- Neuroinflammation and Neurodegeneration Mechanisms
Papers in
- Physiology 13
- Pain Mechanisms and Treatments 12
-
- Pharmacological Effects of Natural Compounds 8
- Healthcare and Venom Research 2
- Co-authors
- Di Zhang (16 shared papers)Shiquan Chang (14 shared papers)Yachun Zheng (15 shared papers)Huimei Shi (12 shared papers)Guoping Zhao (14 shared papers)Zhenni Chen (12 shared papers)Guoqiang Qian (5 shared papers)Xin Li (2 shared papers)
- Journals
- Phytotherapy Research (4 papers)CNS Neuroscience & Therapeutics (2 papers)Journal of Neuroimmune Pharmacology (2 papers)Revista Brasileira de Farmacognosia (1 paper)Phytomedicine (1 paper)
- Partner nations
- China
In The Last Decade
Bei Jing
19 papers receiving 366 citations
Peers
Comparison fields: 5 of 78
- Pharmacology 94
- Neurology 75
- Complementary and alternative medicine 51
- Physiology 127
- Sensory Systems 16
Countries citing papers authored by Bei Jing
This map shows the geographic impact of Bei Jing's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bei Jing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bei Jing more than expected).
Fields of papers citing papers by Bei Jing
This network shows the impact of papers produced by Bei Jing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bei Jing. The network helps show where Bei Jing may publish in the future.
Co-authors
The 25 scholars most cited alongside Bei Jing, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 76 | |
| 2 | 2023 | 60 | |
| 3 | 2023 | 43 | |
| 4 | 2020 | 29 | |
| 5 | 2022 | 27 | |
| 6 | 2022 | 17 | |
| 7 | 2023 | 15 | |
| 8 | 2022 | 15 | |
| 9 | 2023 | 13 | |
| 10 | 2021 | 13 | |
| 11 | 2021 | 9 | |
| 12 | 2023 | 9 | |
| 13 | 2021 | 9 | |
| 14 | 2024 | 8 | |
| 15 | 2022 | 8 | |
| 16 | 2022 | 8 | |
| 17 | 2023 | 6 | |
| 18 | 2025 | 3 | |
| 19 | 2022 | 3 |
About Bei Jing
Bei Jing is a scholar working on Physiology, Pharmacology, Neurology, Pharmacology and Cellular and Molecular Neuroscience, having authored 19 papers that have together received 371 indexed citations. Recurring topics across this work include Pain Mechanisms and Treatments (12 papers), Pharmacological Effects of Natural Compounds (8 papers), Neuroinflammation and Neurodegeneration Mechanisms (6 papers), Healthcare and Venom Research (2 papers), Ion Channels and Receptors (2 papers), Nerve injury and regeneration (1 paper), Forest Biomass Utilization and Management (1 paper) and Botulinum Toxin and Related Neurological Disorders (1 paper). The work is most often cited by research in Pharmacology (94 citations), Neurology (75 citations), Complementary and alternative medicine (51 citations), Physiology (127 citations) and Sensory Systems (16 citations). Bei Jing has collaborated with scholars based in China. Frequent co-authors include Di Zhang, Shiquan Chang, Yachun Zheng, Huimei Shi, Guoping Zhao, Zhenni Chen, Guoqiang Qian, Xin Li, Li Gao and Guoping Zhao. Their work appears in journals such as Phytotherapy Research, CNS Neuroscience & Therapeutics, Journal of Neuroimmune Pharmacology, Revista Brasileira de Farmacognosia and Phytomedicine.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.