Wayne Vuong
Impact in
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
-
- Computational Drug Discovery Methods
Papers in
-
- SARS-CoV-2 and COVID-19 Research 5
- Tuberculosis Research and Epidemiology 2
- Co-authors
- John C. Vederas (8 shared papers)Tess Lamer (5 shared papers)M. Joanne Lemieux (6 shared papers)Muhammad Bashir Khan (5 shared papers)Elena Arutyunova (5 shared papers)Howard S. Young (5 shared papers)D. Lorne Tyrrell (4 shared papers)Conrad Fischer (4 shared papers)
- Journals
- Organic Letters (2 papers)Analytical Chemistry (1 paper)The Journal of Organic Chemistry (1 paper)European Journal of Medicinal Chemistry (1 paper)Chem (1 paper)
- Partner nations
- CanadaUnited States
In The Last Decade
Wayne Vuong
9 papers receiving 530 citations
Peers
Comparison fields: 5 of 60
- Infectious Diseases 328
- Computational Theory and Mathematics 323
- Organic Chemistry 119
- Animal Science and Zoology 34
- Pharmacology 25
Countries citing papers authored by Wayne Vuong
This map shows the geographic impact of Wayne Vuong'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 Wayne Vuong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wayne Vuong more than expected).
Fields of papers citing papers by Wayne Vuong
This network shows the impact of papers produced by Wayne Vuong. 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 Wayne Vuong. The network helps show where Wayne Vuong may publish in the future.
Co-authors
The 25 scholars most cited alongside Wayne Vuong, 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 | 348 | |
| 2 | 2021 | 67 | |
| 3 | 2021 | 40 | |
| 4 | 2021 | 34 | |
| 5 | 2022 | 27 | |
| 6 | 2019 | 10 | |
| 7 | 2023 | 6 | |
| 8 | 2021 | 5 | |
| 9 | 2025 | 1 | |
| 10 | 2025 | 0 |
About Wayne Vuong
Wayne Vuong is a scholar working on Infectious Diseases, Molecular Biology, Computational Theory and Mathematics, Spectroscopy and Animal Science and Zoology, having authored 10 papers that have together received 538 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (5 papers), Computational Drug Discovery Methods (4 papers), Tuberculosis Research and Epidemiology (2 papers), Animal Virus Infections Studies (2 papers), PARP inhibition in cancer therapy (1 paper), Advanced Proteomics Techniques and Applications (1 paper), Pharmacological Effects of Natural Compounds (1 paper) and thermodynamics and calorimetric analyses (1 paper). The work is most often cited by research in Infectious Diseases (328 citations), Computational Theory and Mathematics (323 citations), Organic Chemistry (119 citations), Animal Science and Zoology (34 citations) and Pharmacology (25 citations). Wayne Vuong has collaborated with scholars based in Canada and United States. Frequent co-authors include John C. Vederas, Tess Lamer, M. Joanne Lemieux, Muhammad Bashir Khan, Elena Arutyunova, Howard S. Young, D. Lorne Tyrrell, Conrad Fischer, Marco J. van Belkum and Michael Joyce. Their work appears in journals such as Organic Letters, Analytical Chemistry, The Journal of Organic Chemistry, European Journal of Medicinal Chemistry and Chem.
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.