Teppei Ebina
Impact in
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- Neuroscience and Neuropharmacology Research
- Photoreceptor and optogenetics research
- Neuroscience and Neural Engineering
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
Papers in
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- Machine Learning in Bioinformatics 6
- Protein Structure and Dynamics 5
- RNA and protein synthesis mechanisms 3
- Genomics and Phylogenetic Studies 3
- Retinal Development and Disorders 3
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- Neural dynamics and brain function 7
- Co-authors
- Yutaka Kuroda (7 shared papers)Hiroyuki Toh (2 shared papers)M Matsuzaki (8 shared papers)Kazuhiro Sohya (3 shared papers)Tadaharu Tsumoto (3 shared papers)Yuchio Yanagawa (3 shared papers)Kosuke Maki (1 shared paper)Atsushi Kato (1 shared paper)
In The Last Decade
Teppei Ebina
18 papers receiving 436 citations
Peers
Comparison fields: 5 of 88
- Cellular and Molecular Neuroscience 156
- Cognitive Neuroscience 150
- Biophysics 24
- Molecular Biology 212
- Neurology 25
Countries citing papers authored by Teppei Ebina
This map shows the geographic impact of Teppei Ebina'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 Teppei Ebina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Teppei Ebina more than expected).
Fields of papers citing papers by Teppei Ebina
This network shows the impact of papers produced by Teppei Ebina. 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 Teppei Ebina. The network helps show where Teppei Ebina may publish in the future.
Co-authors
The 25 scholars most cited alongside Teppei Ebina, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 81 | |
| 2 | 2010 | 74 | |
| 3 | 2018 | 60 | |
| 4 | 2010 | 54 | |
| 5 | 2008 | 38 | |
| 6 | 2019 | 33 | |
| 7 | 2014 | 21 | |
| 8 | 2020 | 20 | |
| 9 | 2014 | 16 | |
| 10 | 2021 | 13 | |
| 11 | 2020 | 8 | |
| 12 | 2023 | 7 | |
| 13 | 2014 | 5 | |
| 14 | 2013 | 3 | |
| 15 | 2016 | 2 | |
| 16 | 2024 | 1 | |
| 17 | 2024 | 1 | |
| 18 | 2008 | 1 |
About Teppei Ebina
Teppei Ebina is a scholar working on Molecular Biology, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Cell Biology and Neurology, having authored 18 papers that have together received 438 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (7 papers), Neural dynamics and brain function (7 papers), Machine Learning in Bioinformatics (6 papers), Protein Structure and Dynamics (5 papers), RNA and protein synthesis mechanisms (3 papers), Genomics and Phylogenetic Studies (3 papers), Photoreceptor and optogenetics research (3 papers) and Retinal Development and Disorders (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (156 citations), Cognitive Neuroscience (150 citations), Biophysics (24 citations), Molecular Biology (212 citations) and Neurology (25 citations). Teppei Ebina has collaborated with scholars based in Japan and Iran. Frequent co-authors include Yutaka Kuroda, Hiroyuki Toh, M Matsuzaki, Kazuhiro Sohya, Tadaharu Tsumoto, Yuchio Yanagawa, Kosuke Maki, Atsushi Kato, Kunitsugu Soda and Kunihiro Kuwajima. Their work appears in journals such as Nature Communications, Journal of Computer-Aided Molecular Design, Journal of Neuroscience, Biopolymers and Cell Reports.
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.