Daniel Ellis
Impact in
- Infectious Diseases top 1%
- SARS-CoV-2 and COVID-19 Research
- Virology top 5%
- HIV Research and Treatment
Papers in
-
- SARS-CoV-2 and COVID-19 Research 6
-
- Influenza Virus Research Studies 6
- Co-authors
- Neil P. King (8 shared papers)David Veesler (2 shared papers)Katharine H. D. Crawford (1 shared paper)M. Alejandra Tortorici (1 shared paper)Adam S. Dingens (1 shared paper)Allison J. Greaney (1 shared paper)Mary-Jane Navarro (1 shared paper)Jesse D. Bloom (1 shared paper)
- Journals
- Nature Communications (5 papers)Science Translational Medicine (2 papers)Nature (2 papers)Cell Reports (2 papers)Frontiers in Immunology (1 paper)
- Partner nations
- United StatesNetherlandsAustralia
In The Last Decade
Daniel Ellis
20 papers receiving 2.9k citations
Daniel Ellis's Hit Papers
Peers
Comparison fields: 5 of 61
- Infectious Diseases 1.3k
- Virology 92
- Biomaterials 137
- Epidemiology 213
- Molecular Biology 378
Countries citing papers authored by Daniel Ellis
This map shows the geographic impact of Daniel Ellis'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 Daniel Ellis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Ellis more than expected).
Fields of papers citing papers by Daniel Ellis
This network shows the impact of papers produced by Daniel Ellis. 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 Daniel Ellis. The network helps show where Daniel Ellis may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Ellis, 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 | Deep Mutational Scanning of SARS-CoV-2 Receptor Binding Domain Reveals Constraints on Folding and ACE2 Binding Hit paper breakdown → | 2020 | 1417 |
| 2 | Accurate design of megadalton-scale two-component icosahedral protein complexes Hit paper breakdown → | 2016 | 478 |
| 3 | Quadrivalent influenza nanoparticle vaccines induce broad protection Hit paper breakdown → | 2021 | 234 |
| 4 | 2017 | 169 | |
| 5 | 2019 | 166 | |
| 6 | 2020 | 144 | |
| 7 | 2019 | 55 | |
| 8 | 2022 | 54 | |
| 9 | 2021 | 47 | |
| 10 | 2022 | 41 | |
| 11 | 2022 | 38 | |
| 12 | 2021 | 36 | |
| 13 | 2023 | 26 | |
| 14 | 2023 | 21 | |
| 15 | 2023 | 16 | |
| 16 | 2023 | 15 | |
| 17 | 2025 | 14 | |
| 18 | 2024 | 13 | |
| 19 | 2024 | 10 | |
| 20 | 2025 | 3 |
About Daniel Ellis
Daniel Ellis is a scholar working on Infectious Diseases, Epidemiology, Virology, Biomaterials and Immunology, having authored 20 papers that have together received 3.0k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (6 papers), SARS-CoV-2 and COVID-19 Research (6 papers), Immunotherapy and Immune Responses (1 paper), HIV Research and Treatment (1 paper), Protein Structure and Dynamics (1 paper) and Nanoparticle-Based Drug Delivery (1 paper). The work is most often cited by research in Infectious Diseases (1.3k citations), Virology (92 citations), Biomaterials (137 citations), Epidemiology (213 citations) and Molecular Biology (378 citations). Daniel Ellis has collaborated with scholars based in United States, Netherlands and Australia. Frequent co-authors include Neil P. King, David Veesler, Katharine H. D. Crawford, M. Alejandra Tortorici, Adam S. Dingens, Allison J. Greaney, Mary-Jane Navarro, Jesse D. Bloom, Sarah K. Hilton and Tyler N. Starr. Their work appears in journals such as Nature Communications, Science Translational Medicine, Nature, Cell Reports and Frontiers in Immunology.
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.