Evan E. Seitz
Impact in
- Structural Biology top 5%
- Advanced Electron Microscopy Techniques and Applications
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
Papers in
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- Advanced Electron Microscopy Techniques and Applications 3
-
- Advanced Physical and Chemical Molecular Interactions 1
- Co-authors
- Joachim Frank (4 shared papers)F.J. Acosta-Reyes (2 shared papers)Suvrajit Maji (2 shared papers)James Andrew McCammon (1 shared paper)A. Ourmazd (1 shared paper)Fiona L. Kearns (1 shared paper)Lillian T. Chong (1 shared paper)Ghoncheh Mashayekhi (1 shared paper)
- Journals
- Nature Chemistry (1 paper)Physics Letters B (1 paper)Nature Machine Intelligence (1 paper)Journal of Chemical Information and Modeling (1 paper)IEEE Transactions on Computational Imaging (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Evan E. Seitz
7 papers receiving 336 citations
Evan E. Seitz's Hit Papers
Peers
Comparison fields: 5 of 44
- Structural Biology 29
- Infectious Diseases 186
- Molecular Biology 129
- Physical and Theoretical Chemistry 13
- Computational Theory and Mathematics 18
Countries citing papers authored by Evan E. Seitz
This map shows the geographic impact of Evan E. Seitz'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 Evan E. Seitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Evan E. Seitz more than expected).
Fields of papers citing papers by Evan E. Seitz
This network shows the impact of papers produced by Evan E. Seitz. 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 Evan E. Seitz. The network helps show where Evan E. Seitz may publish in the future.
Co-authors
The 25 scholars most cited alongside Evan E. Seitz, 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 | A glycan gate controls opening of the SARS-CoV-2 spike protein Hit paper breakdown → | 2021 | 293 |
| 2 | 2024 | 17 | |
| 3 | 2022 | 15 | |
| 4 | 2020 | 8 | |
| 5 | 1983 | 4 | |
| 6 | 2023 | 3 | |
| 7 | 2022 | 1 |
About Evan E. Seitz
Evan E. Seitz is a scholar working on Structural Biology, Physical and Theoretical Chemistry, Computational Theory and Mathematics, Nuclear and High Energy Physics and Infectious Diseases, having authored 7 papers that have together received 341 indexed citations. Recurring topics across this work include Advanced Electron Microscopy Techniques and Applications (3 papers), Protein Structure and Dynamics (2 papers), Explainable Artificial Intelligence (XAI) (1 paper), Advanced Physical and Chemical Molecular Interactions (1 paper), Computational Drug Discovery Methods (1 paper), Quantum Chromodynamics and Particle Interactions (1 paper) and SARS-CoV-2 and COVID-19 Research (1 paper). The work is most often cited by research in Structural Biology (29 citations), Infectious Diseases (186 citations), Molecular Biology (129 citations), Physical and Theoretical Chemistry (13 citations) and Computational Theory and Mathematics (18 citations). Evan E. Seitz has collaborated with scholars based in United States and Germany. Frequent co-authors include Joachim Frank, F.J. Acosta-Reyes, Suvrajit Maji, James Andrew McCammon, A. Ourmazd, Fiona L. Kearns, Lillian T. Chong, Ghoncheh Mashayekhi, Jason S. McLellan and Anthony T. Bogetti. Their work appears in journals such as Nature Chemistry, Physics Letters B, Nature Machine Intelligence, Journal of Chemical Information and Modeling and IEEE Transactions on Computational Imaging.
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.