Hirotoshi Kakuta
- Molecular Biology
- Surgery
- Cardiology and Cardiovascular Medicine
- Endocrinology, Diabetes and Metabolism top 10%
- Computational Theory and Mathematics top 10%
- Co-authors
- Tsukasa IshiharaHisataka ShikamaIsao YanagisawaKeiji MiyataToshiyuki TakasuOsamu InagakiToshiyuki FunatsuMotoko Yamaguchi
- Topics
- Computational Drug Discovery Methods (7 papers)Plant biochemistry and biosynthesis (6 papers)Cholesterol and Lipid Metabolism (6 papers)
In The Last Decade
Hirotoshi Kakuta
25 papers receiving 503 citations
Peers
Comparison fields: 5 of 76
- Molecular Biology 221
- Surgery 155
- Cardiology and Cardiovascular Medicine 120
- Endocrinology, Diabetes and Metabolism 109
- Computational Theory and Mathematics 64
Countries citing papers authored by Hirotoshi Kakuta
This map shows the geographic impact of Hirotoshi Kakuta'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 Hirotoshi Kakuta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hirotoshi Kakuta more than expected).
Fields of papers citing papers by Hirotoshi Kakuta
This network shows the impact of papers produced by Hirotoshi Kakuta. 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 Hirotoshi Kakuta. The network helps show where Hirotoshi Kakuta may publish in the future.
Co-authorship network of co-authors of Hirotoshi Kakuta
This figure shows the co-authorship network connecting the top 25 collaborators of Hirotoshi Kakuta. A scholar is included among the top collaborators of Hirotoshi Kakuta based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hirotoshi Kakuta. Hirotoshi Kakuta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 20 | |
| 3 | 2 | |
| 4 | 38 | |
| 5 | 34 | |
| 6 | 2 | |
| 7 | 39 | |
| 8 | 19 | |
| 9 | 15 | |
| 10 | 10 | |
| 11 | 25 | |
| 12 | 13 | |
| 13 | 13 | |
| 14 | 14 | |
| 15 | 16 | |
| 16 | 7 | |
| 17 | 67 | |
| 18 | 32 | |
| 19 | 14 | |
| 20 | [Morphological studies on renal changes with age 1. Glomerular, tubular and interstitial changes (author's transl)]. | 2 |
About Hirotoshi Kakuta
Hirotoshi Kakuta is a scholar working on Pharmacology, Computational Theory and Mathematics and Biochemistry, having authored 25 papers that have together received 531 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Plant biochemistry and biosynthesis (6 papers) and Cholesterol and Lipid Metabolism (6 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (109 citations), Cardiology and Cardiovascular Medicine (120 citations) and Biochemistry (33 citations). Hirotoshi Kakuta has collaborated with scholars based in Japan, Norway and Russia. Frequent co-authors include Tsukasa Ishihara, Hisataka Shikama, Isao Yanagisawa, Keiji Miyata, Toshiyuki Takasu, Osamu Inagaki, Toshiyuki Funatsu, Motoko Yamaguchi, Hiroshi Sasaki and Shintaro Nishimura. Their work appears in journals such as Biochemical and Biophysical Research Communications, Journal of Pharmacology and Experimental Therapeutics and British Journal of Pharmacology.
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.