Cai Read
Impact in
- Pharmacology top 2%
- Apelin-related biomedical research
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- Nuclear Receptors and Signaling
- Neuropeptides and Animal Physiology
Papers in
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- Apelin-related biomedical research 6
-
- Nuclear Receptors and Signaling 3
- Co-authors
- Peiran B Yang (8 shared papers)Anthony P. Davenport (7 shared papers)Janet J. Maguire (7 shared papers)Robert Charles Glen (6 shared papers)Rhoda E. Kuc (6 shared papers)Nicholas W. Morrell (3 shared papers)Stephen J. Sawiak (3 shared papers)Alexi Crosby (3 shared papers)
- Journals
- British Journal of Pharmacology (1 paper)Neuroendocrinology (1 paper)Journal of the American Heart Association (1 paper)Thorax (1 paper)Basic & Clinical Pharmacology & Toxicology (1 paper)
- Partner nations
- United KingdomUnited StatesPortugal
In The Last Decade
Cai Read
10 papers receiving 601 citations
Peers
Comparison fields: 5 of 64
- Pharmacology 369
- Cellular and Molecular Neuroscience 200
- Surgery 252
- Endocrinology, Diabetes and Metabolism 84
- Cardiology and Cardiovascular Medicine 60
Countries citing papers authored by Cai Read
This map shows the geographic impact of Cai Read'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 Cai Read with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cai Read more than expected).
Fields of papers citing papers by Cai Read
This network shows the impact of papers produced by Cai Read. 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 Cai Read. The network helps show where Cai Read may publish in the future.
Co-authors
The 25 scholars most cited alongside Cai Read, 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 | 2017 | 200 | |
| 2 | 2019 | 89 | |
| 3 | 2016 | 78 | |
| 4 | 2016 | 65 | |
| 5 | 2018 | 47 | |
| 6 | 2019 | 41 | |
| 7 | 2021 | 23 | |
| 8 | 2008 | 22 | |
| 9 | 2021 | 21 | |
| 10 | 2019 | 19 |
About Cai Read
Cai Read is a scholar working on Pharmacology, Cellular and Molecular Neuroscience, Endocrinology, Diabetes and Metabolism, Surgery and Rheumatology, having authored 10 papers that have together received 605 indexed citations. Recurring topics across this work include Apelin-related biomedical research (6 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (4 papers), Nuclear Receptors and Signaling (3 papers), Growth Hormone and Insulin-like Growth Factors (1 paper), Diabetes Treatment and Management (1 paper), Adipose Tissue and Metabolism (1 paper), Adipokines, Inflammation, and Metabolic Diseases (1 paper) and GDF15 and Related Biomarkers (1 paper). The work is most often cited by research in Pharmacology (369 citations), Cellular and Molecular Neuroscience (200 citations), Surgery (252 citations), Endocrinology, Diabetes and Metabolism (84 citations) and Cardiology and Cardiovascular Medicine (60 citations). Cai Read has collaborated with scholars based in United Kingdom, United States and Portugal. Frequent co-authors include Peiran B Yang, Anthony P. Davenport, Janet J. Maguire, Robert Charles Glen, Rhoda E. Kuc, Nicholas W. Morrell, Stephen J. Sawiak, Alexi Crosby, Mark R. Southwood and Guido Buonincontri. Their work appears in journals such as British Journal of Pharmacology, Neuroendocrinology, Journal of the American Heart Association, Thorax and Basic & Clinical Pharmacology & Toxicology.
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.