Keisuke Ina
Impact in
- Nephrology top 10%
- Chronic Kidney Disease and Diabetes
- Renal Diseases and Glomerulopathies
-
- Advanced Glycation End Products research
Papers in
-
- Glycosylation and Glycoproteins Research 2
- Genetics 9
- Diabetes and associated disorders 7
- Co-authors
- Hirokazu Kitamura (14 shared papers)Yoshihisa Fujikura (15 shared papers)Tatsuo Shimada (5 shared papers)Junko Ono (7 shared papers)Ryosaburo Takaki (3 shared papers)Toshimitsu Okeda (2 shared papers)H. Kitamura (4 shared papers)Takenobu Shimada (1 shared paper)
- Journals
- Diabetes Research and Clinical Practice (6 papers)Experimental Biology and Medicine (2 papers)Anatomical Science International (2 papers)Cells Tissues Organs (1 paper)PLoS ONE (1 paper)
- Partner nations
- JapanAustraliaUnited States
In The Last Decade
Keisuke Ina
29 papers receiving 315 citations
Peers
Comparison fields: 5 of 74
- Nephrology 58
- Clinical Biochemistry 20
- Surgery 85
- Cardiology and Cardiovascular Medicine 42
- Transplantation 5
Countries citing papers authored by Keisuke Ina
This map shows the geographic impact of Keisuke Ina'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 Keisuke Ina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keisuke Ina more than expected).
Fields of papers citing papers by Keisuke Ina
This network shows the impact of papers produced by Keisuke Ina. 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 Keisuke Ina. The network helps show where Keisuke Ina may publish in the future.
Co-authors
The 25 scholars most cited alongside Keisuke Ina, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 46 | |
| 2 | 1995 | 40 | |
| 3 | 1999 | 36 | |
| 4 | 2011 | 32 | |
| 5 | 1997 | 24 | |
| 6 | 1996 | 17 | |
| 7 | 2015 | 13 | |
| 8 | 1993 | 13 | |
| 9 | 1993 | 12 | |
| 10 | 2015 | 11 | |
| 11 | 1997 | 9 | |
| 12 | 2009 | 8 | |
| 13 | 1991 | 8 | |
| 14 | 2005 | 7 | |
| 15 | 1997 | 6 | |
| 16 | 1999 | 6 | |
| 17 | 2001 | 5 | |
| 18 | 2007 | 5 | |
| 19 | 1994 | 4 | |
| 20 | 2008 | 4 |
About Keisuke Ina
Keisuke Ina is a scholar working on Molecular Biology, Genetics, Surgery, Nephrology and Physiology, having authored 30 papers that have together received 324 indexed citations. Recurring topics across this work include Chronic Kidney Disease and Diabetes (7 papers), Diabetes and associated disorders (7 papers), Pancreatic function and diabetes (6 papers), Renal Diseases and Glomerulopathies (4 papers), Diabetes Management and Research (3 papers), Salivary Gland Disorders and Functions (3 papers), Glycosylation and Glycoproteins Research (2 papers) and Cannabis and Cannabinoid Research (2 papers). The work is most often cited by research in Nephrology (58 citations), Clinical Biochemistry (20 citations), Surgery (85 citations), Cardiology and Cardiovascular Medicine (42 citations) and Transplantation (5 citations). Keisuke Ina has collaborated with scholars based in Japan, Australia and United States. Frequent co-authors include Hirokazu Kitamura, Yoshihisa Fujikura, Tatsuo Shimada, Junko Ono, Ryosaburo Takaki, Toshimitsu Okeda, H. Kitamura, Takenobu Shimada, Tatsuo Shimada and Masahiko Nishimura. Their work appears in journals such as Diabetes Research and Clinical Practice, Experimental Biology and Medicine, Anatomical Science International, Cells Tissues Organs and PLoS ONE.
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.