Ha V. Dang
Impact in
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- Viral Infections and Vectors
- SARS-CoV-2 detection and testing
- COVID-19 Clinical Research Studies
- Epidemiology top 10%
- Virology and Viral Diseases
Papers in
-
- Viral Infections and Vectors 6
- SARS-CoV-2 detection and testing 2
- SARS-CoV-2 and COVID-19 Research 1
-
- Virology and Viral Diseases 8
- Respiratory viral infections research 4
- Co-authors
- David VeeslerLianying YanChristopher C. BroderToru NakabayashiAndrew G. GeiserLing‐Yuan KongN TalalJohn J. Letterio
- Journals
- Science (2 papers)Nature Structural & Molecular Biology (2 papers)Proceedings of the National Academy of Sciences (2 papers)Nature Methods (1 paper)The Journal of Immunology (1 paper)
- Partner nations
- United StatesNetherlandsAustralia
In The Last Decade
Ha V. Dang
16 papers receiving 816 citations
Peers
Comparison fields: 5 of 74
- Infectious Diseases 418
- Epidemiology 255
- Virology 32
- Animal Science and Zoology 61
- Business and International Management 11
Countries citing papers authored by Ha V. Dang
This map shows the geographic impact of Ha V. Dang'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 Ha V. Dang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ha V. Dang more than expected).
Fields of papers citing papers by Ha V. Dang
This network shows the impact of papers produced by Ha V. Dang. 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 Ha V. Dang. The network helps show where Ha V. Dang may publish in the future.
Co-authors
The 25 scholars most cited alongside Ha V. Dang, 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 | 2024 | 8 | |
| 2 | 2022 | 15 | |
| 3 | 2022 | 53 | |
| 4 | 2021 | 172 | |
| 5 | 2021 | 42 | |
| 6 | 2021 | 81 | |
| 7 | 2021 | 23 | |
| 8 | 2021 | 13 | |
| 9 | 2019 | 49 | |
| 10 | 2019 | 71 | |
| 11 | 2019 | 1 | |
| 12 | 2017 | 77 | |
| 13 | 2017 | 2 | |
| 14 | 1997 | 36 | |
| 15 | 1995 | 149 | |
| 16 | 1991 | 40 | |
| 17 | Monoclonal anti-poly(rA) hybridoma antibodies from an autoimmune MRL/MpJ-lpr/lpr mouse. | 1985 | 0 |
About Ha V. Dang
Ha V. Dang is a scholar working on Infectious Diseases, Epidemiology, Virology, Parasitology and Physical and Theoretical Chemistry, having authored 17 papers that have together received 832 indexed citations. Recurring topics across this work include Virology and Viral Diseases (8 papers), Viral Infections and Vectors (6 papers), Respiratory viral infections research (4 papers), Advanced biosensing and bioanalysis techniques (3 papers), vaccines and immunoinformatics approaches (2 papers), Biosensors and Analytical Detection (2 papers), SARS-CoV-2 detection and testing (2 papers) and SARS-CoV-2 and COVID-19 Research (1 paper). The work is most often cited by research in Infectious Diseases (418 citations), Epidemiology (255 citations), Virology (32 citations), Animal Science and Zoology (61 citations) and Business and International Management (11 citations). Ha V. Dang has collaborated with scholars based in United States, Netherlands and Australia. Frequent co-authors include David Veesler, Lianying Yan, Christopher C. Broder, Toru Nakabayashi, Andrew G. Geiser, Ling‐Yuan Kong, N Talal, John J. Letterio, Gustavo Vicentis Oliveira Fernandes and Matthew McCallum. Their work appears in journals such as Science, Nature Structural & Molecular Biology, Proceedings of the National Academy of Sciences, Nature Methods and The Journal of Immunology.
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.