Ken Matsumoto
- Molecular Biology top 1%
- Genetics top 2%
- Cancer Research top 2%
- Immunology top 5%
- Plant Science top 5%
- Co-authors
- Alan P. WolffeYasuhiro GonShu HashimotoMasafumi TsujimotoTakashi HorieIkuko TakeshitaToshihiko OguraKyosuke Nagata
- Topics
- RNA Research and Splicing (31 papers)RNA and protein synthesis mechanisms (14 papers)Heat shock proteins research (14 papers)
- Partner nations
- JapanUnited StatesSingapore
In The Last Decade
Ken Matsumoto
215 papers receiving 7.6k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Molecular Biology 4.9k
- Genetics 1.0k
- Cancer Research 919
- Immunology 800
- Plant Science 617
Countries citing papers authored by Ken Matsumoto
This map shows the geographic impact of Ken Matsumoto'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 Ken Matsumoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Matsumoto more than expected).
Fields of papers citing papers by Ken Matsumoto
This network shows the impact of papers produced by Ken Matsumoto. 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 Ken Matsumoto. The network helps show where Ken Matsumoto may publish in the future.
Co-authorship network of co-authors of Ken Matsumoto
This figure shows the co-authorship network connecting the top 25 collaborators of Ken Matsumoto. A scholar is included among the top collaborators of Ken Matsumoto 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 Ken Matsumoto. Ken Matsumoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 28 | |
| 2 | 3 | |
| 3 | 62 | |
| 4 | 22 | |
| 5 | Javawock: A Java Class Recommender System Based on Collaborative Filtering | 10 |
| 6 | 13 | |
| 7 | 20 | |
| 8 | Effects of β-Blockers on Coronary Spasm Induced by Repeated Epicardial Coronary Artery Endothelial Denudation in Pigs | 3 |
| 9 | FcεRI 架橋後のヒトおよびマウスのマスト細胞トランスクリプトームにおけるC-Cケモカイン遺伝子形質発現の著しい増加 | 1 |
| 10 | 193 | |
| 11 | 41 | |
| 12 | 116 | |
| 13 | 131 | |
| 14 | 14 | |
| 15 | 52 | |
| 16 | Does exercise have a clinically important effect on plasma amino acid concentrations | 1 |
| 17 | 22 | |
| 18 | 134 | |
| 19 | 13 | |
| 20 | The in vitro and in vivo metabolism of delta 6a,10a dimethyl heptyl tetrahydrocannabinol (DMHP). | 3 |
About Ken Matsumoto
Ken Matsumoto is a scholar working on Complementary and Manual Therapy, Molecular Biology and Biochemistry, having authored 222 papers that have together received 7.8k indexed citations. Recurring topics across this work include RNA Research and Splicing (31 papers), RNA and protein synthesis mechanisms (14 papers) and Heat shock proteins research (14 papers). The work is most often cited by research in Molecular Biology (4.9k citations), Cancer Research (919 citations) and Immunology (800 citations). Ken Matsumoto has collaborated with scholars based in Japan, United States and Singapore. Frequent co-authors include Alan P. Wolffe, Yasuhiro Gon, Shu Hashimoto, Masafumi Tsujimoto, Takashi Horie, Ikuko Takeshita, Toshihiko Ogura, Kyosuke Nagata, Shuichiro Maruoka and Masatsugu Ema. Their work appears in journals such as Nature, Science and Cell.
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.