Jay C. Brown
Impact in
- Epidemiology top 0.2%
- Herpesvirus Infections and Treatments
- Cytomegalovirus and herpesvirus research
- Virology top 1%
Papers in
- Epidemiology 76
- Herpesvirus Infections and Treatments 65
- Cytomegalovirus and herpesvirus research 38
- Virology and Viral Diseases 10
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- RNA and protein synthesis mechanisms 10
- Co-authors
- William W. Newcomb (80 shared papers)Benes L. Trus (23 shared papers)Alasdair C. Steven (26 shared papers)Fred L. Homa (19 shared papers)Frank P. Booy (18 shared papers)Richard C. Hunt (7 shared papers)Naiqian Cheng (9 shared papers)Timothy S. Baker (6 shared papers)
- Journals
- Journal of Virology (47 papers)Journal of Molecular Biology (7 papers)Virology (7 papers)Proceedings of the National Academy of Sciences (3 papers)Analytical Biochemistry (2 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Jay C. Brown
118 papers receiving 6.3k citations
Peers
Comparison fields: 5 of 129
- Epidemiology 4.1k
- Virology 572
- Structural Biology 161
- Genetics 1.5k
- Ecology 1.4k
Countries citing papers authored by Jay C. Brown
This map shows the geographic impact of Jay C. Brown'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 Jay C. Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay C. Brown more than expected).
Fields of papers citing papers by Jay C. Brown
This network shows the impact of papers produced by Jay C. Brown. 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 Jay C. Brown. The network helps show where Jay C. Brown may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay C. Brown, 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 121 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1991 | 311 | |
| 2 | 2001 | 257 | |
| 3 | 1991 | 232 | |
| 4 | 1993 | 226 | |
| 5 | 1996 | 205 | |
| 6 | 1985 | 196 | |
| 7 | 1994 | 187 | |
| 8 | 1978 | 167 | |
| 9 | 2003 | 153 | |
| 10 | 1998 | 152 | |
| 11 | 1970 | 150 | |
| 12 | 2004 | 146 | |
| 13 | 2007 | 140 | |
| 14 | 2008 | 138 | |
| 15 | 1991 | 133 | |
| 16 | 2011 | 121 | |
| 17 | 1999 | 112 | |
| 18 | 2000 | 110 | |
| 19 | 2001 | 110 | |
| 20 | 2006 | 104 |
About Jay C. Brown
Jay C. Brown is a scholar working on Epidemiology, Molecular Biology, Ecology, Genetics and Immunology, having authored 121 papers that have together received 6.6k indexed citations. Recurring topics across this work include Herpesvirus Infections and Treatments (65 papers), Cytomegalovirus and herpesvirus research (38 papers), Bacteriophages and microbial interactions (33 papers), Virus-based gene therapy research (25 papers), Toxin Mechanisms and Immunotoxins (21 papers), Plant Virus Research Studies (15 papers), Virology and Viral Diseases (10 papers) and RNA and protein synthesis mechanisms (10 papers). The work is most often cited by research in Epidemiology (4.1k citations), Virology (572 citations), Structural Biology (161 citations), Genetics (1.5k citations) and Ecology (1.4k citations). Jay C. Brown has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include William W. Newcomb, Benes L. Trus, Alasdair C. Steven, Fred L. Homa, Frank P. Booy, Richard C. Hunt, Naiqian Cheng, Timothy S. Baker, Darrell R. Thomsen and Sandra K. Weller. Their work appears in journals such as Journal of Virology, Journal of Molecular Biology, Virology, Proceedings of the National Academy of Sciences and Analytical Biochemistry.
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.