Eric M. Davis
Impact in
- Immunology top 10%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Immunodeficiency and Autoimmune Disorders
- Immunotherapy and Immune Responses
- Cell Biology top 10%
- Cellular transport and secretion
Papers in
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- CRISPR and Genetic Engineering 2
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- Cellular transport and secretion 5
- Co-authors
- Jingshi Shen (6 shared papers)Eric Meffre (2 shared papers)Michel C. Nussenzweig (2 shared papers)Haijia Yu (5 shared papers)Yan Ouyang (3 shared papers)Shailendra S. Rathore (2 shared papers)Hedda Wardemann (1 shared paper)Anne Schaefer (1 shared paper)
- Journals
- Proceedings of the National Academy of Sciences (2 papers)eLife (1 paper)Cell Reports (1 paper)The FASEB Journal (1 paper)Genome biology (1 paper)
- Partner nations
- United StatesChinaFrance
In The Last Decade
Eric M. Davis
15 papers receiving 647 citations
Peers
Comparison fields: 5 of 82
- Immunology 236
- Cell Biology 151
- Parasitology 56
- Physiology 27
- Virology 21
Countries citing papers authored by Eric M. Davis
This map shows the geographic impact of Eric M. Davis'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 Eric M. Davis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric M. Davis more than expected).
Fields of papers citing papers by Eric M. Davis
This network shows the impact of papers produced by Eric M. Davis. 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 Eric M. Davis. The network helps show where Eric M. Davis may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric M. Davis, 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 | 2003 | 109 | |
| 2 | 2000 | 101 | |
| 3 | 2001 | 82 | |
| 4 | 2013 | 64 | |
| 5 | 2017 | 51 | |
| 6 | 2013 | 50 | |
| 7 | 2016 | 41 | |
| 8 | 2021 | 37 | |
| 9 | 2015 | 34 | |
| 10 | 2001 | 28 | |
| 11 | 1978 | 20 | |
| 12 | 2021 | 15 | |
| 13 | 2020 | 13 | |
| 14 | 2018 | 8 | |
| 15 | 2020 | 1 |
About Eric M. Davis
Eric M. Davis is a scholar working on Molecular Biology, Cell Biology, Immunology, Cancer Research and Epidemiology, having authored 15 papers that have together received 654 indexed citations. Recurring topics across this work include Cellular transport and secretion (5 papers), Cancer Genomics and Diagnostics (2 papers), T-cell and B-cell Immunology (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Immune Cell Function and Interaction (2 papers), Parasites and Host Interactions (2 papers), CRISPR and Genetic Engineering (2 papers) and Trypanosoma species research and implications (1 paper). The work is most often cited by research in Immunology (236 citations), Cell Biology (151 citations), Parasitology (56 citations), Physiology (27 citations) and Virology (21 citations). Eric M. Davis has collaborated with scholars based in United States, China and France. Frequent co-authors include Jingshi Shen, Eric Meffre, Michel C. Nussenzweig, Haijia Yu, Yan Ouyang, Shailendra S. Rathore, Hedda Wardemann, Anne Schaefer, Patrick C. Wilson and Thomas A. Wynn. Their work appears in journals such as Proceedings of the National Academy of Sciences, eLife, Cell Reports, The FASEB Journal and Genome 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.