Kiyoshi Masuda
- Molecular Biology top 2%
- Cancer Research top 2%
- Plant Science top 5%
- Immunology top 10%
- Oncology top 10%
- Co-authors
- Yuki KuwanoKazuhito RokutanKensei NishidaIssei ImotoMasumi YamagishiMyriam GorospeShigetada Teshima-KondoTakashi Nakatsuka
- Topics
- RNA Research and Splicing (27 papers)Plant tissue culture and regeneration (20 papers)RNA modifications and cancer (19 papers)
- Partner nations
- JapanUnited StatesSouth Korea
In The Last Decade
Kiyoshi Masuda
144 papers receiving 3.7k citations
Peers
Comparison fields: 5 of 142
- Molecular Biology 2.5k
- Cancer Research 877
- Plant Science 776
- Immunology 416
- Oncology 325
Countries citing papers authored by Kiyoshi Masuda
This map shows the geographic impact of Kiyoshi Masuda'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 Kiyoshi Masuda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kiyoshi Masuda more than expected).
Fields of papers citing papers by Kiyoshi Masuda
This network shows the impact of papers produced by Kiyoshi Masuda. 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 Kiyoshi Masuda. The network helps show where Kiyoshi Masuda may publish in the future.
Co-authorship network of co-authors of Kiyoshi Masuda
This figure shows the co-authorship network connecting the top 25 collaborators of Kiyoshi Masuda. A scholar is included among the top collaborators of Kiyoshi Masuda 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 Kiyoshi Masuda. Kiyoshi Masuda 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 | 5 | |
| 3 | 8 | |
| 4 | 30 | |
| 5 | 7 | |
| 6 | 108 | |
| 7 | 54 | |
| 8 | 1 | |
| 9 | 46 | |
| 10 | 4 | |
| 11 | 21 | |
| 12 | 54 | |
| 13 | 18 | |
| 14 | 98 | |
| 15 | 96 | |
| 16 | Prediction of Sound Transmission Loss by Coupling Analysis of Boundary Element Method and Finite Element Method | 1 |
| 17 | 1 | |
| 18 | Intra-arterial chemotherapy for the treatment of invasive bladder cancer | 1 |
| 19 | Tagged steelhead trout (Salmo gairdneri Richardson) collected in the north Pacific by the Oshoro-Maru, 1982-1985 | 6 |
| 20 | The opportunistic origin of a new citrus pest | 22 |
About Kiyoshi Masuda
Kiyoshi Masuda is a scholar working on Behavioral Neuroscience, Molecular Biology and Cancer Research, having authored 146 papers that have together received 3.9k indexed citations. Recurring topics across this work include RNA Research and Splicing (27 papers), Plant tissue culture and regeneration (20 papers) and RNA modifications and cancer (19 papers). The work is most often cited by research in Cancer Research (877 citations), Molecular Biology (2.5k citations) and Plant Science (776 citations). Kiyoshi Masuda has collaborated with scholars based in Japan, United States and South Korea. Frequent co-authors include Yuki Kuwano, Kazuhito Rokutan, Kensei Nishida, Issei Imoto, Masumi Yamagishi, Myriam Gorospe, Shigetada Teshima-Kondo, Takashi Nakatsuka, Claude E. Boyd and Tomoko Kawai. Their work appears in journals such as Proceedings of the National Academy of Sciences, The EMBO Journal 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.