Will Rowe
Impact in
- Infectious Diseases top 0.5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
Papers in
-
- SARS-CoV-2 and COVID-19 Research 14
- Infection Control in Healthcare 1
-
- COVID-19 epidemiological studies 3
- Co-authors
- Jiajia Zheng (1 shared paper)Richard L. Mackman (1 shared paper)Dhivya Ramakrishnan (1 shared paper)Paul J. Côté (1 shared paper)Michael Mish (1 shared paper)Stéphane Daffis (1 shared paper)Stephan Menne (1 shared paper)Manasa Suresh (1 shared paper)
- Journals
- Nature (3 papers)Nature Communications (2 papers)Scientific Reports (2 papers)BMC Infectious Diseases (1 paper)Journal of Hepatology (1 paper)
- Partner nations
- United Kingdom
In The Last Decade
Will Rowe
15 papers receiving 3.4k citations
Will Rowe's Hit Papers
Peers
Comparison fields: 5 of 100
- Infectious Diseases 3k
- Modeling and Simulation 199
- Neurology 46
- Genetics 89
- Molecular Biology 167
Countries citing papers authored by Will Rowe
This map shows the geographic impact of Will Rowe'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 Will Rowe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Will Rowe more than expected).
Fields of papers citing papers by Will Rowe
This network shows the impact of papers produced by Will Rowe. 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 Will Rowe. The network helps show where Will Rowe may publish in the future.
Co-authors
The 8 scholars most cited alongside Will Rowe, 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 | SARS-CoV-2 evolution during treatment of chronic infection Hit paper breakdown → | 2021 | 814 |
| 2 | 2020 | 756 | |
| 3 | SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway Hit paper breakdown → | 2022 | 571 |
| 4 | Sensitivity of SARS-CoV-2 B.1.1.7 to mRNA vaccine-elicited antibodies Hit paper breakdown → | 2021 | 530 |
| 5 | Recurrent emergence of SARS-CoV-2 spike deletion H69/V70 and its role in the Alpha variant B.1.1.7 Hit paper breakdown → | 2021 | 325 |
| 6 | 2021 | 228 | |
| 7 | 2021 | 72 | |
| 8 | 2021 | 68 | |
| 9 | 2022 | 45 | |
| 10 | 2022 | 31 | |
| 11 | 2017 | 18 | |
| 12 | 2022 | 15 | |
| 13 | 2022 | 13 | |
| 14 | 2022 | 8 | |
| 15 | 2023 | 1 |
About Will Rowe
Will Rowe is a scholar working on Infectious Diseases, Modeling and Simulation, Epidemiology, Molecular Biology and Nuclear Energy and Engineering, having authored 15 papers that have together received 3.5k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (14 papers), COVID-19 epidemiological studies (3 papers), Infection Control in Healthcare (1 paper), Hepatitis B Virus Studies (1 paper) and vaccines and immunoinformatics approaches (1 paper). The work is most often cited by research in Infectious Diseases (3k citations), Modeling and Simulation (199 citations), Neurology (46 citations), Genetics (89 citations) and Molecular Biology (167 citations). Will Rowe has collaborated with scholars based in United Kingdom. Frequent co-authors include Jiajia Zheng, Richard L. Mackman, Dhivya Ramakrishnan, Paul J. Côté, Michael Mish, Stéphane Daffis, Stephan Menne and Manasa Suresh. Their work appears in journals such as Nature, Nature Communications, Scientific Reports, BMC Infectious Diseases and Journal of Hepatology.
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.