Kevin Pearson
Impact in
- Geriatrics and Gerontology top 2%
- Sirtuins and Resveratrol in Medicine
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
Papers in
-
- Chronic Myeloid Leukemia Treatments 2
- Surgery 2
- Cholesterol and Lipid Metabolism 1
- Co-authors
- Rafael de Cabo (4 shared papers)Richard E. Clark (2 shared papers)Lihui Wang (2 shared papers)Daniel Wall (1 shared paper)Virendar K. Kaushik (1 shared paper)Nargis Nasrin (1 shared paper)Laura Bordone (1 shared paper)Anna Csiszár (2 shared papers)
- Journals
- British Journal of Haematology (2 papers)Epilepsy & Behavior (1 paper)Scandinavian Journal of Clinical and Laboratory Investigation (1 paper)Journal of Biological Chemistry (1 paper)Biochemistry (1 paper)
- Partner nations
- United StatesUnited KingdomSweden
In The Last Decade
Kevin Pearson
10 papers receiving 693 citations
Peers
Comparison fields: 5 of 73
- Geriatrics and Gerontology 213
- Aging 52
- Hematology 172
- Genetics 143
- Physiology 40
Countries citing papers authored by Kevin Pearson
This map shows the geographic impact of Kevin Pearson'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 Kevin Pearson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Pearson more than expected).
Fields of papers citing papers by Kevin Pearson
This network shows the impact of papers produced by Kevin Pearson. 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 Kevin Pearson. The network helps show where Kevin Pearson may publish in the future.
Co-authors
The 25 scholars most cited alongside Kevin Pearson, 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 | 2009 | 223 | |
| 2 | 2009 | 207 | |
| 3 | 2003 | 106 | |
| 4 | 2002 | 64 | |
| 5 | 2004 | 35 | |
| 6 | 2020 | 25 | |
| 7 | 2007 | 23 | |
| 8 | 2016 | 12 | |
| 9 | 2011 | 10 | |
| 10 | 2020 | 5 |
About Kevin Pearson
Kevin Pearson is a scholar working on Hematology, Surgery, Molecular Biology, Genetics and Geriatrics and Gerontology, having authored 10 papers that have together received 710 indexed citations. Recurring topics across this work include Chronic Myeloid Leukemia Treatments (2 papers), Chronic Lymphocytic Leukemia Research (2 papers), Sirtuins and Resveratrol in Medicine (2 papers), Eosinophilic Disorders and Syndromes (2 papers), Genetics, Aging, and Longevity in Model Organisms (2 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (1 paper), Cholesterol and Lipid Metabolism (1 paper) and Computational Drug Discovery Methods (1 paper). The work is most often cited by research in Geriatrics and Gerontology (213 citations), Aging (52 citations), Hematology (172 citations), Genetics (143 citations) and Physiology (40 citations). Kevin Pearson has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include Rafael de Cabo, Richard E. Clark, Lihui Wang, Daniel Wall, Virendar K. Kaushik, Nargis Nasrin, Laura Bordone, Anna Csiszár, Zoltán Ungvári and John T. Pinto. Their work appears in journals such as British Journal of Haematology, Epilepsy & Behavior, Scandinavian Journal of Clinical and Laboratory Investigation, Journal of Biological Chemistry and Biochemistry.
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.