Yasushi Okuno
- Molecular Biology top 2%
- Computational Theory and Mathematics top 0.2%
- Oncology top 2%
- Pulmonary and Respiratory Medicine top 2%
- Cancer Research top 2%
- Co-authors
- Kaori KadoyamaToshiyuki SakaedaAkiko TamonGozoh TsujimotoMinoru KanehisaMitsugu ArakiSusumu GotoMasahiro Hattori
- Topics
- Computational Drug Discovery Methods (39 papers)Protein Structure and Dynamics (32 papers)Bioinformatics and Genomic Networks (24 papers)
- Partner nations
- JapanUnited StatesCanada
In The Last Decade
Yasushi Okuno
199 papers receiving 6.6k citations
Hit Papers
Peers
Comparison fields: 5 of 180
- Molecular Biology 3.3k
- Computational Theory and Mathematics 1.2k
- Oncology 1.1k
- Pulmonary and Respiratory Medicine 938
- Cancer Research 677
Countries citing papers authored by Yasushi Okuno
This map shows the geographic impact of Yasushi Okuno'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 Yasushi Okuno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yasushi Okuno more than expected).
Fields of papers citing papers by Yasushi Okuno
This network shows the impact of papers produced by Yasushi Okuno. 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 Yasushi Okuno. The network helps show where Yasushi Okuno may publish in the future.
Co-authorship network of co-authors of Yasushi Okuno
This figure shows the co-authorship network connecting the top 25 collaborators of Yasushi Okuno. A scholar is included among the top collaborators of Yasushi Okuno 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 Yasushi Okuno. Yasushi Okuno is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 5 | |
| 3 | 5 | |
| 4 | 11 | |
| 5 | 8 | |
| 6 | 5 | |
| 7 | 44 | |
| 8 | 8 | |
| 9 | 39 | |
| 10 | 9 | |
| 11 | 15 | |
| 12 | 44 | |
| 13 | Brigatinib combined with anti-EGFR antibody overcomes osimertinib resistance in EGFR-mutated non-small-cell lung cancerbreakdown → | 329 |
| 14 | 19 | |
| 15 | 52 | |
| 16 | 222 | |
| 17 | 255 | |
| 18 | 93 | |
| 19 | 148 | |
| 20 | 7 |
About Yasushi Okuno
Yasushi Okuno is a scholar working on Toxicology, Structural Biology and Computational Theory and Mathematics, having authored 218 papers that have together received 6.7k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (39 papers), Protein Structure and Dynamics (32 papers) and Bioinformatics and Genomic Networks (24 papers). The work is most often cited by research in Toxicology (489 citations), Computational Theory and Mathematics (1.2k citations) and Molecular Biology (3.3k citations). Yasushi Okuno has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Kaori Kadoyama, Toshiyuki Sakaeda, Akiko Tamon, Gozoh Tsujimoto, Minoru Kanehisa, Mitsugu Araki, Susumu Goto, Masahiro Hattori, Ryohei Katayama and Naoya Fujita. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.