Tesia Bobrowski
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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- SARS-CoV-2 and COVID-19 Research 6
- COVID-19 Clinical Research Studies 3
- Viral Infections and Outbreaks Research 2
- Tuberculosis Research and Epidemiology 1
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- Computational Drug Discovery Methods 7
- Co-authors
- Eugene Muratov (10 shared papers)Alexander Tropsha (9 shared papers)Cleber C. Melo‐Filho (5 shared papers)Daniel Korn (6 shared papers)Vinícius M. Alves (5 shared papers)Charles Schmitt (4 shared papers)Scott S. Auerbach (3 shared papers)Nathaniel J. Moorman (3 shared papers)
- Journals
- Journal of Chemical Information and Modeling (2 papers)Molecular Informatics (1 paper)FEMS Microbiology Reviews (1 paper)Microbiology Spectrum (1 paper)Drug Discovery Today (1 paper)
- Partner nations
- United StatesBrazilCanada
In The Last Decade
Tesia Bobrowski
12 papers receiving 252 citations
Peers
Comparison fields: 5 of 62
- Computational Theory and Mathematics 124
- Infectious Diseases 126
- Molecular Biology 94
- Epidemiology 37
- Hepatology 8
Countries citing papers authored by Tesia Bobrowski
This map shows the geographic impact of Tesia Bobrowski'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 Tesia Bobrowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tesia Bobrowski more than expected).
Fields of papers citing papers by Tesia Bobrowski
This network shows the impact of papers produced by Tesia Bobrowski. 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 Tesia Bobrowski. The network helps show where Tesia Bobrowski may publish in the future.
Co-authors
The 25 scholars most cited alongside Tesia Bobrowski, 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 | 2020 | 78 | |
| 2 | 2020 | 64 | |
| 3 | 2020 | 28 | |
| 4 | 2022 | 26 | |
| 5 | 2020 | 15 | |
| 6 | 2023 | 12 | |
| 7 | 2022 | 11 | |
| 8 | 2021 | 6 | |
| 9 | 2025 | 5 | |
| 10 | 2023 | 4 | |
| 11 | 2021 | 3 | |
| 12 | 2020 | 1 | |
| 13 | 2024 | 0 |
About Tesia Bobrowski
Tesia Bobrowski is a scholar working on Infectious Diseases, Computational Theory and Mathematics, Molecular Biology, Cardiology and Cardiovascular Medicine and Organic Chemistry, having authored 13 papers that have together received 253 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 Clinical Research Studies (3 papers), Viral Infections and Outbreaks Research (2 papers), Viral Infections and Immunology Research (2 papers), Pharmacogenetics and Drug Metabolism (1 paper), Tuberculosis Research and Epidemiology (1 paper) and Mosquito-borne diseases and control (1 paper). The work is most often cited by research in Computational Theory and Mathematics (124 citations), Infectious Diseases (126 citations), Molecular Biology (94 citations), Epidemiology (37 citations) and Hepatology (8 citations). Tesia Bobrowski has collaborated with scholars based in United States, Brazil and Canada. Frequent co-authors include Eugene Muratov, Alexander Tropsha, Cleber C. Melo‐Filho, Daniel Korn, Vinícius M. Alves, Charles Schmitt, Scott S. Auerbach, Nathaniel J. Moorman, Alexey Zakharov and Richard T. Eastman. Their work appears in journals such as Journal of Chemical Information and Modeling, Molecular Informatics, FEMS Microbiology Reviews, Microbiology Spectrum and Drug Discovery Today.
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.