Keisuke Ejima
Impact in
- Aging top 0.5%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 1%
- Telomeres, Telomerase, and Senescence
Papers in
-
- COVID-19 epidemiological studies 16
- Virology 13
- HIV Research and Treatment 8
- Co-authors
- Hiroshi Nishiura (22 shared papers)Kazuyuki Aihara (15 shared papers)Shingo Iwami (19 shared papers)David Blair Allison (20 shared papers)Kenji Mizumoto (6 shared papers)Keisuke Kawata (12 shared papers)Kwang Su Kim (10 shared papers)Shoya Iwanami (11 shared papers)
- Journals
- Journal of Theoretical Biology (4 papers)Theoretical Biology and Medical Modelling (4 papers)Scientific Reports (3 papers)Obesity (3 papers)PLoS ONE (3 papers)
- Partner nations
- United StatesJapanSingapore
In The Last Decade
Keisuke Ejima
88 papers receiving 3.5k citations
Keisuke Ejima's Hit Papers
Peers
Comparison fields: 5 of 136
- Aging 443
- Physiology 1.3k
- Modeling and Simulation 219
- Geriatrics and Gerontology 82
- Infectious Diseases 401
Countries citing papers authored by Keisuke Ejima
This map shows the geographic impact of Keisuke Ejima'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 Keisuke Ejima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keisuke Ejima more than expected).
Fields of papers citing papers by Keisuke Ejima
This network shows the impact of papers produced by Keisuke Ejima. 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 Keisuke Ejima. The network helps show where Keisuke Ejima may publish in the future.
Co-authors
The 25 scholars most cited alongside Keisuke Ejima, 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 96 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Senolytics improve physical function and increase lifespan in old age Hit paper breakdown → | 2018 | 1816 |
| 2 | Senolytics reduce coronavirus-related mortality in old mice Hit paper breakdown → | 2021 | 271 |
| 3 | 2021 | 149 | |
| 4 | 2018 | 132 | |
| 5 | 2021 | 120 | |
| 6 | 2021 | 57 | |
| 7 | 2021 | 44 | |
| 8 | 2021 | 37 | |
| 9 | 2018 | 35 | |
| 10 | 2013 | 34 | |
| 11 | 2020 | 34 | |
| 12 | 2020 | 34 | |
| 13 | 2021 | 34 | |
| 14 | 2019 | 33 | |
| 15 | 2014 | 32 | |
| 16 | 2020 | 32 | |
| 17 | 2020 | 31 | |
| 18 | 2016 | 30 | |
| 19 | 2015 | 26 | |
| 20 | 2012 | 24 |
About Keisuke Ejima
Keisuke Ejima is a scholar working on Modeling and Simulation, Virology, Infectious Diseases, Public Health, Environmental and Occupational Health and Statistics and Probability, having authored 96 papers that have together received 3.6k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (16 papers), Traumatic Brain Injury Research (12 papers), Mathematical and Theoretical Epidemiology and Ecology Models (11 papers), SARS-CoV-2 and COVID-19 Research (11 papers), Obesity, Physical Activity, Diet (10 papers), HIV Research and Treatment (8 papers), Statistical Methods in Epidemiology (7 papers) and Influenza Virus Research Studies (5 papers). The work is most often cited by research in Aging (443 citations), Physiology (1.3k citations), Modeling and Simulation (219 citations), Geriatrics and Gerontology (82 citations) and Infectious Diseases (401 citations). Keisuke Ejima has collaborated with scholars based in United States, Japan and Singapore. Frequent co-authors include Hiroshi Nishiura, Kazuyuki Aihara, Shingo Iwami, David Blair Allison, Kenji Mizumoto, Keisuke Kawata, Kwang Su Kim, Shoya Iwanami, Yasuhisa Fujita and Yoshiki Koizumi. Their work appears in journals such as Journal of Theoretical Biology, Theoretical Biology and Medical Modelling, Scientific Reports, Obesity and PLoS ONE.
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.