Lisa E. Gralinski
Impact in
- Infectious Diseases top 0.2%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Viral gastroenteritis research and epidemiology
- SARS-CoV-2 detection and testing
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
Papers in
-
- SARS-CoV-2 and COVID-19 Research 30
- Viral gastroenteritis research and epidemiology 9
- COVID-19 Clinical Research Studies 8
-
- Animal Virus Infections Studies 11
- Co-authors
- Vineet D. MenacheryRalph S. BaricBoyd L. YountSudhakar AgnihothramTrevor ScobeyRachel L. GrahamMark T. HeiseTimothy P. Sheahan
- Journals
- mBio (7 papers)Journal of Virology (7 papers)G3 Genes Genomes Genetics (3 papers)Proceedings of the National Academy of Sciences (3 papers)BMC Systems Biology (2 papers)
- Partner nations
- United StatesJapanUnited Kingdom
In The Last Decade
Lisa E. Gralinski
51 papers receiving 5.8k citations
Hit Papers
Peers
Comparison fields: 5 of 154
- Infectious Diseases 4.1k
- Modeling and Simulation 383
- Animal Science and Zoology 834
- Neurology 809
- Immunology 981
Countries citing papers authored by Lisa E. Gralinski
This map shows the geographic impact of Lisa E. Gralinski'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 Lisa E. Gralinski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lisa E. Gralinski more than expected).
Fields of papers citing papers by Lisa E. Gralinski
This network shows the impact of papers produced by Lisa E. Gralinski. 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 Lisa E. Gralinski. The network helps show where Lisa E. Gralinski may publish in the future.
Co-authors
The 25 scholars most cited alongside Lisa E. Gralinski, 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 | Understanding COVID-19-associated coagulopathy Hit paper breakdown → | 2022 | 191 |
| 2 | 2021 | 18 | |
| 3 | 2021 | 7 | |
| 4 | 2020 | 52 | |
| 5 | 2020 | 332 | |
| 6 | 2020 | 381 | |
| 7 | 2020 | 2 | |
| 8 | 2017 | 86 | |
| 9 | 2017 | 19 | |
| 10 | 2016 | 48 | |
| 11 | A SARS-like cluster of circulating bat coronaviruses shows potential for human emergence Hit paper breakdown → | 2015 | 560 |
| 12 | 2015 | 101 | |
| 13 | 2015 | 36 | |
| 14 | 2014 | 81 | |
| 15 | 2013 | 81 | |
| 16 | 2013 | 15 | |
| 17 | 2010 | 214 | |
| 18 | 2009 | 58 | |
| 19 | 2007 | 6 | |
| 20 | 2006 | 16 |
About Lisa E. Gralinski
Lisa E. Gralinski is a scholar working on Infectious Diseases, Animal Science and Zoology, Immunology, Modeling and Simulation and Epidemiology, having authored 53 papers that have together received 5.9k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (30 papers), Animal Virus Infections Studies (11 papers), Viral gastroenteritis research and epidemiology (9 papers), interferon and immune responses (9 papers), Influenza Virus Research Studies (9 papers), COVID-19 Clinical Research Studies (8 papers), Respiratory viral infections research (7 papers) and Virus-based gene therapy research (4 papers). The work is most often cited by research in Infectious Diseases (4.1k citations), Modeling and Simulation (383 citations), Animal Science and Zoology (834 citations), Neurology (809 citations) and Immunology (981 citations). Lisa E. Gralinski has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Vineet D. Menachery, Ralph S. Baric, Boyd L. Yount, Sudhakar Agnihothram, Trevor Scobey, Rachel L. Graham, Mark T. Heise, Timothy P. Sheahan, Sarah R. Leist and Alan C. Whitmore. Their work appears in journals such as mBio, Journal of Virology, G3 Genes Genomes Genetics, Proceedings of the National Academy of Sciences and BMC Systems 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.