Jun Kusunoki
Impact in
-
- Diet, Metabolism, and Disease
- Biochemistry top 5%
- Lipid metabolism and biosynthesis
Papers in
- Surgery 15
- Cholesterol and Lipid Metabolism 15
- Lipoproteins and Cardiovascular Health 6
-
- Cancer, Lipids, and Metabolism 4
- Co-authors
- Katsumi Aragane (13 shared papers)Hideaki Bujo (5 shared papers)Hiroyuki Yamazaki (4 shared papers)Yasushi Saitō (4 shared papers)Shawn C. Burgess (2 shared papers)Norma N. Anderson (2 shared papers)Stanisław Deja (2 shared papers)Chai-Wan Kim (2 shared papers)
- Journals
- Arteriosclerosis Thrombosis and Vascular Biology (4 papers)Cell Metabolism (2 papers)Atherosclerosis (2 papers)Biochemical and Biophysical Research Communications (2 papers)Circulation (1 paper)
- Partner nations
- JapanUnited StatesBelgium
In The Last Decade
Jun Kusunoki
32 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 90
- Endocrinology, Diabetes and Metabolism 293
- Biochemistry 135
- Cancer Research 244
- Epidemiology 381
- Cell Biology 183
Countries citing papers authored by Jun Kusunoki
This map shows the geographic impact of Jun Kusunoki'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 Kusunoki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Kusunoki more than expected).
Fields of papers citing papers by Jun Kusunoki
This network shows the impact of papers produced by Jun Kusunoki. 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 Kusunoki. The network helps show where Jun Kusunoki may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Kusunoki, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 357 | |
| 2 | 1996 | 180 | |
| 3 | 1993 | 120 | |
| 4 | 2007 | 111 | |
| 5 | 2001 | 96 | |
| 6 | 2017 | 93 | |
| 7 | 2006 | 86 | |
| 8 | 1997 | 59 | |
| 9 | 1988 | 48 | |
| 10 | 2012 | 45 | |
| 11 | 2000 | 41 | |
| 12 | 2008 | 36 | |
| 13 | 2009 | 33 | |
| 14 | 1991 | 32 | |
| 15 | 2012 | 30 | |
| 16 | 2004 | 28 | |
| 17 | 2001 | 25 | |
| 18 | 2013 | 22 | |
| 19 | 1995 | 20 | |
| 20 | 2001 | 16 |
About Jun Kusunoki
Jun Kusunoki is a scholar working on Surgery, Cancer Research, Biochemistry, Molecular Biology and Physiology, having authored 32 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cholesterol and Lipid Metabolism (15 papers), Peroxisome Proliferator-Activated Receptors (7 papers), Lipoproteins and Cardiovascular Health (6 papers), Lipid metabolism and biosynthesis (4 papers), Adipose Tissue and Metabolism (4 papers), Liver Disease Diagnosis and Treatment (4 papers), Cancer, Lipids, and Metabolism (4 papers) and RNA and protein synthesis mechanisms (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (293 citations), Biochemistry (135 citations), Cancer Research (244 citations), Epidemiology (381 citations) and Cell Biology (183 citations). Jun Kusunoki has collaborated with scholars based in Japan, United States and Belgium. Frequent co-authors include Katsumi Aragane, Hideaki Bujo, Hiroyuki Yamazaki, Yasushi Saitō, Shawn C. Burgess, Norma N. Anderson, Stanisław Deja, Chai-Wan Kim, Manu V. Chakravarthy and David E. Kelley. Their work appears in journals such as Arteriosclerosis Thrombosis and Vascular Biology, Cell Metabolism, Atherosclerosis, Biochemical and Biophysical Research Communications and Circulation.
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.