Daniel Ellis
Impact in
- Infectious Diseases top 1%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
- Structural Biology top 10%
Papers in
-
- RNA and protein synthesis mechanisms 2
- Ecology 4
- Bacteriophages and microbial interactions 4
- Co-authors
- Neil P. King (8 shared papers)David Veesler (2 shared papers)Jesse D. Bloom (1 shared paper)Sarah K. Hilton (1 shared paper)Tyler N. Starr (1 shared paper)M. Alejandra Tortorici (1 shared paper)Katharine H. D. Crawford (1 shared paper)Alexandra C. Walls (1 shared paper)
- Journals
- Cell Reports (2 papers)Journal of Pharmacology and Experimental Therapeutics (1 paper)Nature Communications (1 paper)Nature (1 paper)Cell (1 paper)
- Partner nations
- United StatesNetherlands
In The Last Decade
Daniel Ellis
10 papers receiving 1.8k citations
Daniel Ellis's Hit Papers
Peers
Comparison fields: 5 of 98
- Infectious Diseases 1000
- Structural Biology 23
- Animal Science and Zoology 159
- Molecular Biology 961
- Ecology 340
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 | 1158 |
| 2 | Accurate design of megadalton-scale two-component icosahedral protein complexes Hit paper breakdown → | 2016 | 418 |
| 3 | 2017 | 153 | |
| 4 | 2019 | 45 | |
| 5 | 2021 | 38 | |
| 6 | 2023 | 17 | |
| 7 | 2023 | 11 | |
| 8 | 1993 | 10 | |
| 9 | 2024 | 9 | |
| 10 | 1995 | 4 |
About Daniel Ellis
Daniel Ellis is a scholar working on Molecular Biology, Ecology, Infectious Diseases, Genetics and Epidemiology, having authored 10 papers that have together received 1.9k indexed citations. Recurring topics across this work include Bacteriophages and microbial interactions (4 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), RNA and protein synthesis mechanisms (2 papers), Immune Cell Function and Interaction (1 paper), Virus-based gene therapy research (1 paper), Pickering emulsions and particle stabilization (1 paper) and Advanced Proteomics Techniques and Applications (1 paper). The work is most often cited by research in Infectious Diseases (1000 citations), Structural Biology (23 citations), Animal Science and Zoology (159 citations), Molecular Biology (961 citations) and Ecology (340 citations). Daniel Ellis has collaborated with scholars based in United States and Netherlands. Frequent co-authors include Neil P. King, David Veesler, Jesse D. Bloom, Sarah K. Hilton, Tyler N. Starr, M. Alejandra Tortorici, Katharine H. D. Crawford, Alexandra C. Walls, Adam S. Dingens and Mary Jane Navarro. Their work appears in journals such as Cell Reports, Journal of Pharmacology and Experimental Therapeutics, Nature Communications, Nature and Cell.
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.