Dai Wang
Impact in
- Parasitology top 1%
- Toxoplasma gondii Research Studies
- Epidemiology top 1%
- Cytomegalovirus and herpesvirus research
- Herpesvirus Infections and Treatments
Papers in ⓘ
- Epidemiology 48
- Cytomegalovirus and herpesvirus research 39
- Herpesvirus Infections and Treatments 33
- Genetics 26
- Genetic Associations and Epidemiology 10
- Virus-based gene therapy research 6
- Co-authors
- Thomas Shenk (6 shared papers)Tong‐Ming Fu (27 shared papers)Colin R. Parrish (4 shared papers)Daniel C. Freed (26 shared papers)Andrew J. Roe (10 shared papers)Xueqin Lin (2 shared papers)David L. Gally (8 shared papers)Fengsheng Li (17 shared papers)
- Journals
- Journal of Virology (12 papers)Vaccine (6 papers)Proceedings of the National Academy of Sciences (5 papers)Virology (4 papers)Journal of Geographical Sciences (3 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Dai Wang
105 papers receiving 4.9k citations
Peers
Comparison fields: 5 of 147
- Parasitology 593
- Epidemiology 2.5k
- Infectious Diseases 1.1k
- Endocrinology 298
- Virology 258
Countries citing papers authored by Dai Wang
This map shows the geographic impact of Dai Wang'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 Dai Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dai Wang more than expected).
Fields of papers citing papers by Dai Wang
This network shows the impact of papers produced by Dai Wang. 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 Dai Wang. The network helps show where Dai Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Dai Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 490 | |
| 2 | 2005 | 414 | |
| 3 | 2005 | 294 | |
| 4 | 2001 | 186 | |
| 5 | 2012 | 129 | |
| 6 | 2002 | 121 | |
| 7 | 2001 | 117 | |
| 8 | 2007 | 116 | |
| 9 | 2008 | 116 | |
| 10 | 2013 | 111 | |
| 11 | 2004 | 105 | |
| 12 | 2005 | 97 | |
| 13 | 2015 | 96 | |
| 14 | 2016 | 91 | |
| 15 | 2017 | 89 | |
| 16 | 2003 | 87 | |
| 17 | 2011 | 82 | |
| 18 | 2019 | 79 | |
| 19 | 2007 | 74 | |
| 20 | 2017 | 73 |
About Dai Wang
Dai Wang is a scholar working on Epidemiology, Genetics, Infectious Diseases, Molecular Biology and Immunology, having authored 105 papers that have together received 5.0k indexed citations. Recurring topics across this work include Cytomegalovirus and herpesvirus research (39 papers), Herpesvirus Infections and Treatments (33 papers), Genetic Associations and Epidemiology (10 papers), Toxoplasma gondii Research Studies (10 papers), Parvovirus B19 Infection Studies (9 papers), Escherichia coli research studies (7 papers), Viral gastroenteritis research and epidemiology (7 papers) and Virus-based gene therapy research (6 papers). The work is most often cited by research in Parasitology (593 citations), Epidemiology (2.5k citations), Infectious Diseases (1.1k citations), Endocrinology (298 citations) and Virology (258 citations). Dai Wang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Thomas Shenk, Tong‐Ming Fu, Colin R. Parrish, Daniel C. Freed, Andrew J. Roe, Xueqin Lin, David L. Gally, Fengsheng Li, Zhiqiang An and Aimin Tang. Their work appears in journals such as Journal of Virology, Vaccine, Proceedings of the National Academy of Sciences, Virology and Journal of Geographical Sciences.
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.