Yasuo Tabei
Impact in
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- Computational Drug Discovery Methods
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- RNA and protein synthesis mechanisms
- Bioinformatics and Genomic Networks
- Genomics and Phylogenetic Studies
- Protein Structure and Dynamics
- RNA modifications and cancer
- Machine Learning in Bioinformatics
Papers in
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- Algorithms and Data Compression 24
- Natural Language Processing Techniques 8
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- RNA and protein synthesis mechanisms 5
- Genomics and Phylogenetic Studies 5
- Co-authors
- Yoshihiro Yamanishi (14 shared papers)Kiyoshi Asai (4 shared papers)Taishin Kin (3 shared papers)Hisanori Kiryu (2 shared papers)Masaaki Kotera (8 shared papers)Koji Tsuda (6 shared papers)Susumu Goto (4 shared papers)Hiroshi Sakamoto (7 shared papers)
In The Last Decade
Yasuo Tabei
54 papers receiving 781 citations
Peers
Comparison fields: 5 of 93
- Computational Theory and Mathematics 273
- Molecular Biology 492
- Artificial Intelligence 167
- Hardware and Architecture 31
- Statistical and Nonlinear Physics 48
Countries citing papers authored by Yasuo Tabei
This map shows the geographic impact of Yasuo Tabei'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 Yasuo Tabei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yasuo Tabei more than expected).
Fields of papers citing papers by Yasuo Tabei
This network shows the impact of papers produced by Yasuo Tabei. 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 Yasuo Tabei. The network helps show where Yasuo Tabei may publish in the future.
Co-authors
The 25 scholars most cited alongside Yasuo Tabei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 98 | |
| 2 | 2012 | 76 | |
| 3 | 2007 | 61 | |
| 4 | 2017 | 53 | |
| 5 | 2018 | 44 | |
| 6 | 2006 | 40 | |
| 7 | 2013 | 36 | |
| 8 | 2013 | 35 | |
| 9 | 2013 | 28 | |
| 10 | 2019 | 23 | |
| 11 | 2011 | 21 | |
| 12 | 2013 | 21 | |
| 13 | 2015 | 17 | |
| 14 | 2016 | 17 | |
| 15 | 2019 | 16 | |
| 16 | 2013 | 16 | |
| 17 | 2020 | 14 | |
| 18 | 2014 | 13 | |
| 19 | 2016 | 12 | |
| 20 | 2014 | 12 |
About Yasuo Tabei
Yasuo Tabei is a scholar working on Artificial Intelligence, Molecular Biology, Computational Theory and Mathematics, Signal Processing and Computer Vision and Pattern Recognition, having authored 55 papers that have together received 796 indexed citations. Recurring topics across this work include Algorithms and Data Compression (24 papers), Computational Drug Discovery Methods (11 papers), Data Management and Algorithms (8 papers), Natural Language Processing Techniques (8 papers), Network Packet Processing and Optimization (7 papers), Advanced Image and Video Retrieval Techniques (6 papers), RNA and protein synthesis mechanisms (5 papers) and Genomics and Phylogenetic Studies (5 papers). The work is most often cited by research in Computational Theory and Mathematics (273 citations), Molecular Biology (492 citations), Artificial Intelligence (167 citations), Hardware and Architecture (31 citations) and Statistical and Nonlinear Physics (48 citations). Yasuo Tabei has collaborated with scholars based in Japan, Finland and Denmark. Frequent co-authors include Yoshihiro Yamanishi, Kiyoshi Asai, Taishin Kin, Hisanori Kiryu, Masaaki Kotera, Koji Tsuda, Susumu Goto, Hiroshi Sakamoto, Kazuhiro Takemoto and Véronique Stoven. Their work appears in journals such as Bioinformatics, BMC Systems Biology, Information and Computation, Molecular Informatics and Lecture notes in computer science.
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.