Danielle E. Dorosky
Impact in
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
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- Computational Drug Discovery Methods
Papers in
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- Viral Infections and Outbreaks Research 2
- SARS-CoV-2 and COVID-19 Research 1
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- Advanced biosensing and bioanalysis techniques 1
- Cell death mechanisms and regulation 1
- Co-authors
- John M. Dye (4 shared papers)Erik Procko (1 shared paper)Shawn A. Abbasi (1 shared paper)David M. Kranz (1 shared paper)Preeti Sharma (1 shared paper)Kui K. Chan (1 shared paper)Andrew S. Herbert (1 shared paper)Laura I. Prugar (3 shared papers)
- Journals
- The Journal of Immunology (1 paper)Antiviral Research (1 paper)Science (1 paper)Cell Reports (1 paper)Journal of Medicinal Chemistry (1 paper)
- Partner nations
- United StatesBelgiumBrazil
In The Last Decade
Danielle E. Dorosky
5 papers receiving 459 citations
Danielle E. Dorosky's Hit Papers
Peers
Comparison fields: 5 of 59
- Infectious Diseases 339
- Computational Theory and Mathematics 68
- Animal Science and Zoology 37
- Molecular Biology 195
- Immunology 54
Countries citing papers authored by Danielle E. Dorosky
This map shows the geographic impact of Danielle E. Dorosky'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 Danielle E. Dorosky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle E. Dorosky more than expected).
Fields of papers citing papers by Danielle E. Dorosky
This network shows the impact of papers produced by Danielle E. Dorosky. 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 Danielle E. Dorosky. The network helps show where Danielle E. Dorosky may publish in the future.
Co-authors
The 25 scholars most cited alongside Danielle E. Dorosky, 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 | Engineering human ACE2 to optimize binding to the spike protein of SARS coronavirus 2 Hit paper breakdown → | 2020 | 389 |
| 2 | 2019 | 42 | |
| 3 | 2022 | 18 | |
| 4 | 2020 | 12 | |
| 5 | 2018 | 2 |
About Danielle E. Dorosky
Danielle E. Dorosky is a scholar working on Infectious Diseases, Molecular Biology, Public Health, Environmental and Occupational Health, Immunology and Virology, having authored 5 papers that have together received 463 indexed citations. Recurring topics across this work include Viral Infections and Outbreaks Research (2 papers), Mosquito-borne diseases and control (2 papers), Advanced biosensing and bioanalysis techniques (1 paper), HIV Research and Treatment (1 paper), interferon and immune responses (1 paper), Cell death mechanisms and regulation (1 paper), Hepatitis B Virus Studies (1 paper) and SARS-CoV-2 and COVID-19 Research (1 paper). The work is most often cited by research in Infectious Diseases (339 citations), Computational Theory and Mathematics (68 citations), Animal Science and Zoology (37 citations), Molecular Biology (195 citations) and Immunology (54 citations). Danielle E. Dorosky has collaborated with scholars based in United States, Belgium and Brazil. Frequent co-authors include John M. Dye, Erik Procko, Shawn A. Abbasi, David M. Kranz, Preeti Sharma, Kui K. Chan, Andrew S. Herbert, Laura I. Prugar, Jennifer M. Brannan and Shirit Einav. Their work appears in journals such as The Journal of Immunology, Antiviral Research, Science, Cell Reports and Journal of Medicinal Chemistry.
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.