Iseki Takamoto
- Molecular Biology top 10%
- Epidemiology top 5%
- Physiology top 5%
- Surgery top 10%
- Endocrinology, Diabetes and Metabolism top 5%
- Co-authors
- Naoto KubotaTakashi KadowakiKohjiro UekiTetsuya KubotaYasuo TerauchiToshimasa YamauchiMasao MoroiTetsuo Noda
- Topics
- Pancreatic function and diabetes (14 papers)Adipokines, Inflammation, and Metabolic Diseases (8 papers)Metabolism, Diabetes, and Cancer (8 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryJournal of Clinical Investigation
- Partner nations
- JapanIndiaUnited Kingdom
In The Last Decade
Iseki Takamoto
31 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 112
- Molecular Biology 738
- Epidemiology 595
- Physiology 518
- Surgery 490
- Endocrinology, Diabetes and Metabolism 429
Countries citing papers authored by Iseki Takamoto
This map shows the geographic impact of Iseki Takamoto'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 Iseki Takamoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iseki Takamoto more than expected).
Fields of papers citing papers by Iseki Takamoto
This network shows the impact of papers produced by Iseki Takamoto. 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 Iseki Takamoto. The network helps show where Iseki Takamoto may publish in the future.
Co-authorship network of co-authors of Iseki Takamoto
This figure shows the co-authorship network connecting the top 25 collaborators of Iseki Takamoto. A scholar is included among the top collaborators of Iseki Takamoto 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 Iseki Takamoto. Iseki Takamoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 59 | |
| 3 | 34 | |
| 4 | 37 | |
| 5 | 93 | |
| 6 | 9 | |
| 7 | 18 | |
| 8 | 44 | |
| 9 | 35 | |
| 10 | 11 | |
| 11 | 73 | |
| 12 | 228 | |
| 13 | 62 | |
| 14 | [New diagnostic criteria of diabetes mellitus in Japan, 2010]. | 1 |
| 15 | 10 | |
| 16 | 40 | |
| 17 | 48 | |
| 18 | 269 | |
| 19 | [Diabetes and osteoporosis]. | 9 |
| 20 | 189 |
About Iseki Takamoto
Iseki Takamoto is a scholar working on Endocrinology, Diabetes and Metabolism, Endocrine and Autonomic Systems and Surgery, having authored 31 papers that have together received 1.7k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (14 papers), Adipokines, Inflammation, and Metabolic Diseases (8 papers) and Metabolism, Diabetes, and Cancer (8 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (429 citations), Endocrine and Autonomic Systems (167 citations) and Physiology (518 citations). Iseki Takamoto has collaborated with scholars based in Japan, India and United Kingdom. Frequent co-authors include Naoto Kubota, Takashi Kadowaki, Kohjiro Ueki, Tetsuya Kubota, Yasuo Terauchi, Toshimasa Yamauchi, Masao Moroi, Tetsuo Noda, Wataru Yano and Kazuyuki Tobe. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.
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.