Jun Eguchi
Impact in
- Nephrology top 2%
- Chronic Kidney Disease and Diabetes
- Physiology top 2%
- Adipose Tissue and Metabolism
Papers in
-
- Diabetes Treatment and Management 8
- Epidemiology 18
- Adipokines, Inflammation, and Metabolic Diseases 11
- Co-authors
- Jun Wada (53 shared papers)Hirofumi Makino (28 shared papers)Evan D. Rosen (7 shared papers)Atsuko Nakatsuka (32 shared papers)Kenichi Shikata (16 shared papers)Kazuyuki Hida (12 shared papers)Daisuke Ogawa (14 shared papers)Songtao Yu (2 shared papers)
- Journals
- Diabetes (6 papers)Scientific Reports (5 papers)PLoS ONE (4 papers)Journal of the American Society of Nephrology (3 papers)Frontiers in Endocrinology (3 papers)
- Partner nations
- JapanUnited StatesChina
In The Last Decade
Jun Eguchi
73 papers receiving 3.9k citations
Jun Eguchi's Hit Papers
Peers
Comparison fields: 5 of 116
- Nephrology 313
- Physiology 935
- Endocrinology, Diabetes and Metabolism 582
- Epidemiology 1.1k
- Endocrine and Autonomic Systems 173
Countries citing papers authored by Jun Eguchi
This map shows the geographic impact of Jun Eguchi'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 Jun Eguchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Eguchi more than expected).
Fields of papers citing papers by Jun Eguchi
This network shows the impact of papers produced by Jun Eguchi. 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 Jun Eguchi. The network helps show where Jun Eguchi may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Eguchi, 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 76 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 613 | |
| 2 | Transcriptional Control of Adipose Lipid Handling by IRF4 Hit paper breakdown → | 2011 | 496 |
| 3 | 2014 | 303 | |
| 4 | 2016 | 157 | |
| 5 | 2014 | 149 | |
| 6 | 2008 | 120 | |
| 7 | 2012 | 117 | |
| 8 | 2013 | 112 | |
| 9 | 2008 | 104 | |
| 10 | 2006 | 87 | |
| 11 | 2013 | 80 | |
| 12 | 2016 | 79 | |
| 13 | 2023 | 77 | |
| 14 | 2011 | 74 | |
| 15 | 2015 | 69 | |
| 16 | 1974 | 66 | |
| 17 | 2023 | 65 | |
| 18 | 2018 | 64 | |
| 19 | 2006 | 64 | |
| 20 | 2012 | 63 |
About Jun Eguchi
Jun Eguchi is a scholar working on Endocrinology, Diabetes and Metabolism, Epidemiology, Clinical Biochemistry, Nephrology and Physiology, having authored 76 papers that have together received 4.0k indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (11 papers), Adipose Tissue and Metabolism (11 papers), Diabetes Treatment and Management (8 papers), Chronic Kidney Disease and Diabetes (6 papers), Advanced Glycation End Products research (6 papers), Diabetes and associated disorders (5 papers), RNA Research and Splicing (5 papers) and Galectins and Cancer Biology (5 papers). The work is most often cited by research in Nephrology (313 citations), Physiology (935 citations), Endocrinology, Diabetes and Metabolism (582 citations), Epidemiology (1.1k citations) and Endocrine and Autonomic Systems (173 citations). Jun Eguchi has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Jun Wada, Hirofumi Makino, Evan D. Rosen, Atsuko Nakatsuka, Kenichi Shikata, Kazuyuki Hida, Daisuke Ogawa, Songtao Yu, Izumi Hashimoto and Sanae Teshigawara. Their work appears in journals such as Diabetes, Scientific Reports, PLoS ONE, Journal of the American Society of Nephrology and Frontiers in Endocrinology.
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.