Kiyomi Sato
- Molecular Biology top 2%
- Pharmacology top 0.5%
- Cancer Research top 5%
- Oncology top 10%
- Genetics top 5%
- Co-authors
- Shigeki TsuchidaKimihiko SatohAkio KitaharaNobuyuki ItoIchiro HatayamaMasae TatematsuTakashi IshikawaYasushi Soma
- Topics
- Glutathione Transferases and Polymorphisms (38 papers)Genomics, phytochemicals, and oxidative stress (28 papers)Glycogen Storage Diseases and Myoclonus (12 papers)
- Journals
- ScienceCancerCancer Research
- Partner nations
- JapanUnited StatesGermany
In The Last Decade
Kiyomi Sato
80 papers receiving 3.3k citations
Peers
Comparison fields: 5 of 105
- Molecular Biology 2.7k
- Pharmacology 533
- Cancer Research 517
- Oncology 450
- Genetics 362
Countries citing papers authored by Kiyomi Sato
This map shows the geographic impact of Kiyomi Sato'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 Kiyomi Sato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kiyomi Sato more than expected).
Fields of papers citing papers by Kiyomi Sato
This network shows the impact of papers produced by Kiyomi Sato. 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 Kiyomi Sato. The network helps show where Kiyomi Sato may publish in the future.
Co-authorship network of co-authors of Kiyomi Sato
This figure shows the co-authorship network connecting the top 25 collaborators of Kiyomi Sato. A scholar is included among the top collaborators of Kiyomi Sato 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 Kiyomi Sato. Kiyomi Sato is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 15 | |
| 3 | 21 | |
| 4 | 27 | |
| 5 | 65 | |
| 6 | 20 | |
| 7 | 24 | |
| 8 | 36 | |
| 9 | 53 | |
| 10 | 93 | |
| 11 | 6 | |
| 12 | 23 | |
| 13 | 101 | |
| 14 | 6 | |
| 15 | 82 | |
| 16 | 57 | |
| 17 | 8 | |
| 18 | Comparison of the various forms of glutathione S-transferase with glucose-6-phosphate dehydrogenase and gamma-glutamyltranspeptidase as markers of preneoplastic and neoplastic lesions in rat kidney induced by N-ethyl-N-hydroxyethylnitrosamine. | 22 |
| 19 | Purification of γ-Glutamyltransferases from Rat Hepatomas and Hyperplastic Hepatic Nodules, and Comparison with the Enzyme from Rat Kidney | 54 |
| 20 | 36 |
About Kiyomi Sato
Kiyomi Sato is a scholar working on Biochemistry, Pharmacology and Molecular Biology, having authored 82 papers that have together received 3.5k indexed citations. Recurring topics across this work include Glutathione Transferases and Polymorphisms (38 papers), Genomics, phytochemicals, and oxidative stress (28 papers) and Glycogen Storage Diseases and Myoclonus (12 papers). The work is most often cited by research in Pharmacology (533 citations), Biochemistry (344 citations) and Molecular Biology (2.7k citations). Kiyomi Sato has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Shigeki Tsuchida, Kimihiko Satoh, Akio Kitahara, Nobuyuki Ito, Ichiro Hatayama, Masae Tatematsu, Takashi Ishikawa, Yasushi Soma, Yukinori Mera and Malcolm A Moore. Their work appears in journals such as Science, Cancer and Cancer Research.
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.