Kai Mo
Impact in
- Physiology top 5%
- Pain Mechanisms and Treatments
-
- Nerve injury and regeneration
- Neuropeptides and Animal Physiology
- Hereditary Neurological Disorders
Papers in
- Physiology 10
- Pain Mechanisms and Treatments 10
-
- Cancer-related gene regulation 2
- Co-authors
- Shaogen Wu (13 shared papers)Yuan‐Xiang Tao (13 shared papers)Alex Bekker (11 shared papers)Lingli Liang (9 shared papers)Xiyao Gu (7 shared papers)Brianna Marie Lutz (5 shared papers)Jian‐Yuan Zhao (4 shared papers)Linlin Sun (4 shared papers)
- Journals
- Molecular Pain (2 papers)Pain (2 papers)Journal of Neuroscience (2 papers)Nature Communications (2 papers)Frontiers in Pharmacology (1 paper)
- Partner nations
- ChinaUnited StatesNetherlands
In The Last Decade
Kai Mo
31 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 103
- Physiology 564
- Cellular and Molecular Neuroscience 276
- Anesthesiology and Pain Medicine 48
- Pharmacology 100
- Neurology 81
Countries citing papers authored by Kai Mo
This map shows the geographic impact of Kai Mo'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 Kai Mo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Mo more than expected).
Fields of papers citing papers by Kai Mo
This network shows the impact of papers produced by Kai Mo. 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 Kai Mo. The network helps show where Kai Mo may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai Mo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 160 | |
| 2 | 2016 | 82 | |
| 3 | 2016 | 77 | |
| 4 | 2020 | 76 | |
| 5 | 2017 | 76 | |
| 6 | 2019 | 66 | |
| 7 | 2017 | 57 | |
| 8 | 2016 | 49 | |
| 9 | 2019 | 49 | |
| 10 | 2018 | 46 | |
| 11 | 2024 | 40 | |
| 12 | 2022 | 38 | |
| 13 | 2018 | 36 | |
| 14 | 2016 | 35 | |
| 15 | 2017 | 33 | |
| 16 | 2019 | 25 | |
| 17 | 2016 | 24 | |
| 18 | 2016 | 24 | |
| 19 | 2019 | 18 | |
| 20 | 2018 | 9 |
About Kai Mo
Kai Mo is a scholar working on Physiology, Molecular Biology, Cellular and Molecular Neuroscience, Oncology and Automotive Engineering, having authored 31 papers that have together received 1.0k indexed citations. Recurring topics across this work include Pain Mechanisms and Treatments (10 papers), Hereditary Neurological Disorders (4 papers), Nerve injury and regeneration (3 papers), Advanced Battery Technologies Research (2 papers), Pain Management and Opioid Use (2 papers), Cancer-related gene regulation (2 papers), Advancements in Battery Materials (2 papers) and Botulinum Toxin and Related Neurological Disorders (2 papers). The work is most often cited by research in Physiology (564 citations), Cellular and Molecular Neuroscience (276 citations), Anesthesiology and Pain Medicine (48 citations), Pharmacology (100 citations) and Neurology (81 citations). Kai Mo has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Shaogen Wu, Yuan‐Xiang Tao, Alex Bekker, Lingli Liang, Xiyao Gu, Brianna Marie Lutz, Jian‐Yuan Zhao, Linlin Sun, Fidelis E. Atianjoh and Xuerong Miao. Their work appears in journals such as Molecular Pain, Pain, Journal of Neuroscience, Nature Communications and Frontiers in Pharmacology.
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.