Kun Ma
Impact in
- Rehabilitation top 2%
- Exercise and Physiological Responses
- Cell Biology top 5%
- Muscle metabolism and nutrition
Papers in
-
- Neuroinflammation and Neurodegeneration Mechanisms 6
-
- Adipose Tissue and Metabolism 3
- Adenosine and Purinergic Signaling 3
- Co-authors
- Shalender BhasinNéstor F. González-CadavidWayne E. TaylorCon MallidisJorge ArtazaVahid Pirhajati MahabadiBehrouz SalehianJosé L. Arias
- Journals
- Journal of Cellular Physiology (2 papers)Journal of Investigative Dermatology (2 papers)Plant Biotechnology Journal (2 papers)Science China Life Sciences (2 papers)American Journal of Physiology-Endocrinology and Metabolism (2 papers)
- Partner nations
- ChinaUnited StatesDenmark
In The Last Decade
Kun Ma
56 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 121
- Rehabilitation 214
- Cell Biology 361
- Aging 35
- Physiology 492
- Molecular Biology 1.3k
Countries citing papers authored by Kun Ma
This map shows the geographic impact of Kun Ma'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 Kun Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Ma more than expected).
Fields of papers citing papers by Kun Ma
This network shows the impact of papers produced by Kun Ma. 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 Kun Ma. The network helps show where Kun Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Ma, 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 | 2026 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 3 | |
| 5 | 2022 | 20 | |
| 6 | 2022 | 63 | |
| 7 | 2021 | 6 | |
| 8 | 2020 | 38 | |
| 9 | 2020 | 21 | |
| 10 | 2020 | 23 | |
| 11 | 2019 | 34 | |
| 12 | 2018 | 45 | |
| 13 | 2017 | 11 | |
| 14 | 2017 | 3 | |
| 15 | 2016 | 27 | |
| 16 | 2016 | 16 | |
| 17 | 2015 | 33 | |
| 18 | 2012 | 54 | |
| 19 | 2012 | 4 | |
| 20 | 2002 | 92 |
About Kun Ma
Kun Ma is a scholar working on Neurology, Physiology, Rehabilitation, Aging and Geriatrics and Gerontology, having authored 57 papers that have together received 2.0k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (6 papers), Neuroinflammation and Neurodegeneration Mechanisms (6 papers), Autophagy in Disease and Therapy (6 papers), CRISPR and Genetic Engineering (5 papers), Retinoids in leukemia and cellular processes (3 papers), Peroxisome Proliferator-Activated Receptors (3 papers), Adipose Tissue and Metabolism (3 papers) and Adenosine and Purinergic Signaling (3 papers). The work is most often cited by research in Rehabilitation (214 citations), Cell Biology (361 citations), Aging (35 citations), Physiology (492 citations) and Molecular Biology (1.3k citations). Kun Ma has collaborated with scholars based in China, United States and Denmark. Frequent co-authors include Shalender Bhasin, Néstor F. González-Cadavid, Wayne E. Taylor, Con Mallidis, Jorge Artaza, Vahid Pirhajati Mahabadi, Behrouz Salehian, José L. Arias, Ruoqing Shen and Shereen Ezzat. Their work appears in journals such as Journal of Cellular Physiology, Journal of Investigative Dermatology, Plant Biotechnology Journal, Science China Life Sciences and American Journal of Physiology-Endocrinology and Metabolism.
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.