William W. Hannon
- Infectious Diseases top 2%
- Molecular Biology
- Radiology, Nuclear Medicine and Imaging top 10%
- Epidemiology
- Animal Science and Zoology top 5%
- Co-authors
- Jesse D. BloomAllison J. GreaneyTyler N. StarrAmin AddetiaManish C. ChoudharyJonathan Z. LiAdam S. DingensDavid Veesler
- Topics
- SARS-CoV-2 and COVID-19 Research (5 papers)vaccines and immunoinformatics approaches (3 papers)Influenza Virus Research Studies (2 papers)
- Journals
- ScienceCellMolecular Cell
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
William W. Hannon
12 papers receiving 921 citations
Hit Papers
Peers
Comparison fields: 5 of 66
- Infectious Diseases 684
- Molecular Biology 441
- Radiology, Nuclear Medicine and Imaging 142
- Epidemiology 97
- Animal Science and Zoology 88
Countries citing papers authored by William W. Hannon
This map shows the geographic impact of William W. Hannon'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 William W. Hannon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William W. Hannon more than expected).
Fields of papers citing papers by William W. Hannon
This network shows the impact of papers produced by William W. Hannon. 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 William W. Hannon. The network helps show where William W. Hannon may publish in the future.
Co-authorship network of co-authors of William W. Hannon
This figure shows the co-authorship network connecting the top 25 collaborators of William W. Hannon. A scholar is included among the top collaborators of William W. Hannon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with William W. Hannon. William W. Hannon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 10 | |
| 3 | 5 | |
| 4 | 11 | |
| 5 | A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spikebreakdown → | 85 |
| 6 | 19 | |
| 7 | 10 | |
| 8 | Shifting mutational constraints in the SARS-CoV-2 receptor-binding domain during viral evolutionbreakdown → | 157 |
| 9 | 9 | |
| 10 | 85 | |
| 11 | Prospective mapping of viral mutations that escape antibodies used to treat COVID-19breakdown → | 448 |
| 12 | 68 |
About William W. Hannon
William W. Hannon is a scholar working on Infectious Diseases, Biophysics and Molecular Biology, having authored 12 papers that have together received 929 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (5 papers), vaccines and immunoinformatics approaches (3 papers) and Influenza Virus Research Studies (2 papers). The work is most often cited by research in Infectious Diseases (684 citations), Animal Science and Zoology (88 citations) and Modeling and Simulation (39 citations). William W. Hannon has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Jesse D. Bloom, Allison J. Greaney, Tyler N. Starr, Amin Addetia, Manish C. Choudhary, Jonathan Z. Li, Adam S. Dingens, David Veesler, Bernadeta Dadonaite and Ariana Ghez Farrell. Their work appears in journals such as Science, Cell and Molecular 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.