Gary Ewart

1.8k citations
24 papers · 1.4k · h-index 15

Impact in

  • Virology top 2%
    • HIV Research and Treatment
    • SARS-CoV-2 and COVID-19 Research
    • HIV/AIDS drug development and treatment
    • Viral gastroenteritis research and epidemiology

Papers in

Gary Ewart

24 papers receiving 1.3k citations

Peers

Gary Ewart
Comparison fields: 5 of 86
  • Virology 364
  • Infectious Diseases 702
  • Animal Science and Zoology 230
  • Hepatology 118
  • Epidemiology 331
Replace Masashi Tatsumi with:
Masashi Tatsumi Japan
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Tijana Ivanovic United States
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Simon P. Tucker United States
Stephen W. Mason Canada
Selena M. Sagan Canada
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Gary Ewart relative to Masashi Tatsumi Japan Masashi Tatsumi's profile →
Citations per field
00.5×5.6×
Masashi Tatsumi · 1×
Citations per year

Countries citing papers authored by Gary Ewart

Since Specialization
Citations

This map shows the geographic impact of Gary Ewart'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 Gary Ewart with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gary Ewart more than expected).

Fields of papers citing papers by Gary Ewart

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gary Ewart. 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 Gary Ewart. The network helps show where Gary Ewart may publish in the future.

Co-authors

The 25 scholars most cited alongside Gary Ewart, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gary Ewart Line = papers co-authored together Gary Ewart links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004219
2 1996216
3 2006161
4 1996102
5 2002101
6 200294
7 201074
8 199964
9 200759
10 200954
11 200447
12 201638
13 199231
14 200618
15 198917
16 202014
17 201513
18 200011
19 20168
20 20107

About Gary Ewart

Gary Ewart is a scholar working on Infectious Diseases, Molecular Biology, Virology, Animal Science and Zoology and Epidemiology, having authored 24 papers that have together received 1.4k indexed citations. Recurring topics across this work include HIV Research and Treatment (9 papers), HIV/AIDS drug development and treatment (9 papers), Animal Virus Infections Studies (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Metalloenzymes and iron-sulfur proteins (3 papers), HIV/AIDS Research and Interventions (3 papers), Mosquito-borne diseases and control (3 papers) and Hepatitis C virus research (2 papers). The work is most often cited by research in Virology (364 citations), Infectious Diseases (702 citations), Animal Science and Zoology (230 citations), Hepatology (118 citations) and Epidemiology (331 citations). Gary Ewart has collaborated with scholars based in Australia, United States and Thailand. Frequent co-authors include Peter W. Gage, G B Cox, Lauren E. Wilson, Tara D. Sutherland, Carolyn A. Luscombe, Michelle Miller, John Wilkinson, Kerry Mills, Ronald C. Weir and Eva Lee. Their work appears in journals such as Virology, Journal of Virology, Antimicrobial Agents and Chemotherapy, Analytical and Bioanalytical Chemistry and Advances in experimental medicine and biology.

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.

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