Gen‐ichi Atsumi
- Molecular Biology top 5%
- Physiology top 5%
- Epidemiology top 5%
- Pharmacology top 2%
- Cancer Research top 5%
- Co-authors
- Ichiro KudoMakoto MurakamiYoshihito NakataniKeizo InoueCem Z. GörgünGökhan S. HotamışlıgilRex A. ParkerKeita Kono
- Topics
- Peroxisome Proliferator-Activated Receptors (10 papers)Protein Kinase Regulation and GTPase Signaling (7 papers)Inflammatory mediators and NSAID effects (7 papers)
- Partner nations
- JapanUnited StatesGermany
In The Last Decade
Gen‐ichi Atsumi
43 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Molecular Biology 1.8k
- Physiology 610
- Epidemiology 532
- Pharmacology 499
- Cancer Research 437
Countries citing papers authored by Gen‐ichi Atsumi
This map shows the geographic impact of Gen‐ichi Atsumi'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 Gen‐ichi Atsumi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gen‐ichi Atsumi more than expected).
Fields of papers citing papers by Gen‐ichi Atsumi
This network shows the impact of papers produced by Gen‐ichi Atsumi. 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 Gen‐ichi Atsumi. The network helps show where Gen‐ichi Atsumi may publish in the future.
Co-authorship network of co-authors of Gen‐ichi Atsumi
This figure shows the co-authorship network connecting the top 25 collaborators of Gen‐ichi Atsumi. A scholar is included among the top collaborators of Gen‐ichi Atsumi 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 Gen‐ichi Atsumi. Gen‐ichi Atsumi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 3 | |
| 3 | 9 | |
| 4 | 6 | |
| 5 | 3 | |
| 6 | 11 | |
| 7 | 24 | |
| 8 | 22 | |
| 9 | 23 | |
| 10 | Treatment of diabetes and atherosclerosis by inhibiting fatty-acid-binding protein aP2breakdown → | 599 |
| 11 | 71 | |
| 12 | 26 | |
| 13 | 58 | |
| 14 | 73 | |
| 15 | 148 | |
| 16 | Influence of coenzyme A-independent transacylase and cyclooxygenase inhibitors on the proliferation of breast cancer cells. | 28 |
| 17 | 157 | |
| 18 | 7 | |
| 19 | 193 | |
| 20 | 17 |
About Gen‐ichi Atsumi
Gen‐ichi Atsumi is a scholar working on Biochemistry, Hematology and Pharmacology, having authored 43 papers that have together received 3.0k indexed citations. Recurring topics across this work include Peroxisome Proliferator-Activated Receptors (10 papers), Protein Kinase Regulation and GTPase Signaling (7 papers) and Inflammatory mediators and NSAID effects (7 papers). The work is most often cited by research in Biochemistry (256 citations), Pharmacology (499 citations) and Cancer Research (437 citations). Gen‐ichi Atsumi has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Ichiro Kudo, Makoto Murakami, Yoshihito Nakatani, Keizo Inoue, Cem Z. Görgün, Gökhan S. Hotamışlıgil, Rex A. Parker, Keita Kono, Masato Furuhashi and Floyd H. Chilton. Their work appears in journals such as Nature, Journal of Biological Chemistry and The Journal of Immunology.
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.