Raphael R. Eguchi
Impact in
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- Ion Channels and Receptors
Papers in
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- Protein Structure and Dynamics 4
- Machine Learning in Bioinformatics 1
- RNA and protein synthesis mechanisms 1
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- Enzyme Structure and Function 4
- Co-authors
- Po‐Ssu Huang (6 shared papers)Christian A. Choe (1 shared paper)Namrata Anand (3 shared papers)Alexander Derry (1 shared paper)Russ B. Altman (1 shared paper)Irimpan I. Mathews (1 shared paper)Nassima Oumata (1 shared paper)Vytautas P. Bindokas (1 shared paper)
- Journals
- Nature Chemical Biology (1 paper)PLoS Computational Biology (1 paper)Nature Communications (1 paper)Bioinformatics (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United StatesFrance
In The Last Decade
Raphael R. Eguchi
7 papers receiving 272 citations
Peers
Comparison fields: 5 of 67
- Sensory Systems 23
- Structural Biology 6
- Molecular Biology 203
- Computational Theory and Mathematics 39
- Biophysics 11
Countries citing papers authored by Raphael R. Eguchi
This map shows the geographic impact of Raphael R. Eguchi'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 Raphael R. Eguchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphael R. Eguchi more than expected).
Fields of papers citing papers by Raphael R. Eguchi
This network shows the impact of papers produced by Raphael R. Eguchi. 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 Raphael R. Eguchi. The network helps show where Raphael R. Eguchi may publish in the future.
Co-authors
The 25 scholars most cited alongside Raphael R. Eguchi, 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 | 2022 | 92 | |
| 2 | 2022 | 68 | |
| 3 | 2015 | 54 | |
| 4 | Fully differentiable full-atom protein backbone generation | 2019 | 24 |
| 5 | 2021 | 17 | |
| 6 | 2019 | 11 | |
| 7 | 2022 | 8 |
About Raphael R. Eguchi
Raphael R. Eguchi is a scholar working on Molecular Biology, Materials Chemistry, Structural Biology, Condensed Matter Physics and Cardiology and Cardiovascular Medicine, having authored 7 papers that have together received 274 indexed citations. Recurring topics across this work include Enzyme Structure and Function (4 papers), Protein Structure and Dynamics (4 papers), Peptidase Inhibition and Analysis (1 paper), Machine Learning in Bioinformatics (1 paper), Cell Image Analysis Techniques (1 paper), Cystic Fibrosis Research Advances (1 paper), RNA and protein synthesis mechanisms (1 paper) and Micro and Nano Robotics (1 paper). The work is most often cited by research in Sensory Systems (23 citations), Structural Biology (6 citations), Molecular Biology (203 citations), Computational Theory and Mathematics (39 citations) and Biophysics (11 citations). Raphael R. Eguchi has collaborated with scholars based in United States and France. Frequent co-authors include Po‐Ssu Huang, Christian A. Choe, Namrata Anand, Alexander Derry, Russ B. Altman, Irimpan I. Mathews, Nassima Oumata, Vytautas P. Bindokas, Hervé Galons and Anjaparavanda P. Naren. Their work appears in journals such as Nature Chemical Biology, PLoS Computational Biology, Nature Communications, Bioinformatics 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.