Tsutomu Kabashima
- Molecular Biology top 5%
- Oncology top 5%
- Surgery top 10%
- Endocrinology, Diabetes and Metabolism top 5%
- Cellular and Molecular Neuroscience top 10%
- Co-authors
- Kosaku UyedaTakumi KawaguchiTadashi YoshimotoKiyonori ItoMasaaki KaiBrian E. WadzinskiMakoto TakenoshitaTakayuki Shibata
- Topics
- Peptidase Inhibition and Analysis (17 papers)Advanced biosensing and bioanalysis techniques (13 papers)Neuropeptides and Animal Physiology (12 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryAngewandte Chemie International Edition
- Partner nations
- JapanChinaBangladesh
In The Last Decade
Tsutomu Kabashima
63 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 104
- Molecular Biology 1.3k
- Oncology 533
- Surgery 515
- Endocrinology, Diabetes and Metabolism 279
- Cellular and Molecular Neuroscience 268
Countries citing papers authored by Tsutomu Kabashima
This map shows the geographic impact of Tsutomu Kabashima'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 Tsutomu Kabashima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tsutomu Kabashima more than expected).
Fields of papers citing papers by Tsutomu Kabashima
This network shows the impact of papers produced by Tsutomu Kabashima. 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 Tsutomu Kabashima. The network helps show where Tsutomu Kabashima may publish in the future.
Co-authorship network of co-authors of Tsutomu Kabashima
This figure shows the co-authorship network connecting the top 25 collaborators of Tsutomu Kabashima. A scholar is included among the top collaborators of Tsutomu Kabashima 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 Tsutomu Kabashima. Tsutomu Kabashima is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 3 | |
| 5 | 24 | |
| 6 | 2 | |
| 7 | 11 | |
| 8 | 11 | |
| 9 | 9 | |
| 10 | 9 | |
| 11 | 38 | |
| 12 | 28 | |
| 13 | 335 | |
| 14 | 25 | |
| 15 | 27 | |
| 16 | 3 | |
| 17 | 5 | |
| 18 | 16 | |
| 19 | 21 | |
| 20 | 32 |
About Tsutomu Kabashima
Tsutomu Kabashima is a scholar working on Oncology, Cellular and Molecular Neuroscience and Molecular Biology, having authored 63 papers that have together received 2.1k indexed citations. Recurring topics across this work include Peptidase Inhibition and Analysis (17 papers), Advanced biosensing and bioanalysis techniques (13 papers) and Neuropeptides and Animal Physiology (12 papers). The work is most often cited by research in Biochemistry (174 citations), Oncology (533 citations) and Molecular Biology (1.3k citations). Tsutomu Kabashima has collaborated with scholars based in Japan, China and Bangladesh. Frequent co-authors include Kosaku Uyeda, Takumi Kawaguchi, Tadashi Yoshimoto, Kiyonori Ito, Masaaki Kai, Brian E. Wadzinski, Makoto Takenoshita, Takayuki Shibata, Hiromi Yamashita and Kiyoshi Osatomi. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Angewandte Chemie International Edition.
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.