John Y. Jun
Impact in
- Epidemiology top 5%
- Adipokines, Inflammation, and Metabolic Diseases
- Liver Disease Diagnosis and Treatment
- Physiology top 5%
- Adipose Tissue and Metabolism
Papers in ⓘ
-
- Diet, Metabolism, and Disease 2
- Co-authors
- Jason K. Kim (8 shared papers)Hwi Jin Ko (6 shared papers)Zhiyou Zhang (4 shared papers)Roger J. Davis (2 shared papers)Guadalupe Sabio (2 shared papers)Tamera Barrett (2 shared papers)Alfonso Mora (2 shared papers)Dae Young Jung (7 shared papers)
- Journals
- Diabetes (4 papers)American Journal of Physiology-Endocrinology and Metabolism (3 papers)Breast Cancer Research and Treatment (2 papers)American Journal of Physiology-Cell Physiology (2 papers)Cell Metabolism (1 paper)
- Partner nations
- United StatesAustraliaEgypt
In The Last Decade
John Y. Jun
20 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 82
- Epidemiology 582
- Physiology 403
- Endocrine and Autonomic Systems 94
- Cell Biology 223
- Endocrinology, Diabetes and Metabolism 204
Countries citing papers authored by John Y. Jun
This map shows the geographic impact of John Y. Jun'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 John Y. Jun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Y. Jun more than expected).
Fields of papers citing papers by John Y. Jun
This network shows the impact of papers produced by John Y. Jun. 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 John Y. Jun. The network helps show where John Y. Jun may publish in the future.
Co-authors
The 25 scholars most cited alongside John Y. Jun, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 491 | |
| 2 | 2009 | 148 | |
| 3 | 2009 | 128 | |
| 4 | 2009 | 125 | |
| 5 | 2007 | 57 | |
| 6 | 2012 | 57 | |
| 7 | 2013 | 55 | |
| 8 | 2010 | 54 | |
| 9 | 2011 | 43 | |
| 10 | 2016 | 37 | |
| 11 | 2011 | 36 | |
| 12 | 2012 | 29 | |
| 13 | 2010 | 23 | |
| 14 | 2007 | 10 | |
| 15 | 2020 | 10 | |
| 16 | 2020 | 8 | |
| 17 | 2025 | 5 | |
| 18 | 2006 | 5 | |
| 19 | 2018 | 3 | |
| 20 | 2008 | 1 |
About John Y. Jun
John Y. Jun is a scholar working on Endocrine and Autonomic Systems, Endocrinology, Diabetes and Metabolism, Biochemistry, Sensory Systems and Surgery, having authored 23 papers that have together received 1.3k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (7 papers), Adipose Tissue and Metabolism (5 papers), Adipokines, Inflammation, and Metabolic Diseases (5 papers), Diet, Metabolism, and Disease (2 papers), Metabolism, Diabetes, and Cancer (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Epigenetics and DNA Methylation (2 papers) and Diabetes and associated disorders (2 papers). The work is most often cited by research in Epidemiology (582 citations), Physiology (403 citations), Endocrine and Autonomic Systems (94 citations), Cell Biology (223 citations) and Endocrinology, Diabetes and Metabolism (204 citations). John Y. Jun has collaborated with scholars based in United States, Australia and Egypt. Frequent co-authors include Jason K. Kim, Hwi Jin Ko, Zhiyou Zhang, Roger J. Davis, Guadalupe Sabio, Tamera Barrett, Alfonso Mora, Dae Young Jung, Madhumita Das and Lakshman Segar. Their work appears in journals such as Diabetes, American Journal of Physiology-Endocrinology and Metabolism, Breast Cancer Research and Treatment, American Journal of Physiology-Cell Physiology and Cell 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.