Anna Carbery
Impact in
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- Computational Drug Discovery Methods
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
Papers in
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- Computational Drug Discovery Methods 6
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- Protein Structure and Dynamics 4
- RNA and protein synthesis mechanisms 2
- Renal and related cancers 1
- Co-authors
- Charlotte Mary Deane (4 shared papers)Frank von Delft (3 shared papers)R. Skyner (2 shared papers)Payel Das (1 shared paper)Nathan Brown (1 shared paper)Vijil Chenthamarakshan (1 shared paper)Daniel Allen Nissley (1 shared paper)
- Journals
- Nature Communications (1 paper)Science (1 paper)Journal of Medicinal Chemistry (1 paper)Journal of Chemical Information and Modeling (1 paper)Bioinformatics (1 paper)
- Partner nations
- United KingdomUnited StatesIsrael
In The Last Decade
Anna Carbery
8 papers receiving 801 citations
Anna Carbery's Hit Papers
Peers
Comparison fields: 5 of 102
- Computational Theory and Mathematics 381
- Infectious Diseases 282
- Molecular Biology 385
- Organic Chemistry 125
- Structural Biology 5
Countries citing papers authored by Anna Carbery
This map shows the geographic impact of Anna Carbery'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 Anna Carbery with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna Carbery more than expected).
Fields of papers citing papers by Anna Carbery
This network shows the impact of papers produced by Anna Carbery. 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 Anna Carbery. The network helps show where Anna Carbery may publish in the future.
Co-authors
The 7 scholars most cited alongside Anna Carbery, 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 | Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease Hit paper breakdown → | 2020 | 416 |
| 2 | 2021 | 195 | |
| 3 | Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors Hit paper breakdown → | 2023 | 118 |
| 4 | 2023 | 31 | |
| 5 | 2022 | 29 | |
| 6 | 2023 | 18 | |
| 7 | 2024 | 16 | |
| 8 | 2021 | 4 |
About Anna Carbery
Anna Carbery is a scholar working on Computational Theory and Mathematics, Molecular Biology, Pharmacology, Infectious Diseases and Nephrology, having authored 8 papers that have together received 827 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Protein Structure and Dynamics (4 papers), Microbial Natural Products and Biosynthesis (2 papers), RNA and protein synthesis mechanisms (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Renal and related cancers (1 paper), Monoclonal and Polyclonal Antibodies Research (1 paper) and Chronic Kidney Disease and Diabetes (1 paper). The work is most often cited by research in Computational Theory and Mathematics (381 citations), Infectious Diseases (282 citations), Molecular Biology (385 citations), Organic Chemistry (125 citations) and Structural Biology (5 citations). Anna Carbery has collaborated with scholars based in United Kingdom, United States and Israel. Frequent co-authors include Charlotte Mary Deane, Frank von Delft, R. Skyner, Payel Das, Nathan Brown, Vijil Chenthamarakshan and Daniel Allen Nissley. Their work appears in journals such as Nature Communications, Science, Journal of Medicinal Chemistry, Journal of Chemical Information and Modeling and Bioinformatics.
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.