George D. Pearson
Impact in
- Genetics top 5%
- Virus-based gene therapy research
- Molecular Biology top 10%
- Viral Infectious Diseases and Gene Expression in Insects
- Insect Resistance and Genetics
- Redox biology and oxidative stress
- CRISPR and Genetic Engineering
Papers in
-
- Social Media and Politics 6
- Genetics 25
- Virus-based gene therapy research 20
- Co-authors
- Gary F. MerrillDavid H. CoombsGeorge F RohrmannMargot PearsonPhilip C. HanawaltKai WangJohn W. BodnarH. Mark Engelking
- Journals
- Virology (7 papers)Proceedings of the National Academy of Sciences (6 papers)Gene (3 papers)Nucleic Acids Research (2 papers)New Media & Society (2 papers)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
George D. Pearson
47 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 119
- Genetics 422
- Molecular Biology 828
- Communication 72
- Insect Science 91
- Infectious Diseases 131
Countries citing papers authored by George D. Pearson
This map shows the geographic impact of George D. Pearson'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 George D. Pearson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George D. Pearson more than expected).
Fields of papers citing papers by George D. Pearson
This network shows the impact of papers produced by George D. Pearson. 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 George D. Pearson. The network helps show where George D. Pearson may publish in the future.
Co-authors
The 25 scholars most cited alongside George D. Pearson, 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 | 2025 | 1 | |
| 2 | 2024 | 10 | |
| 3 | 2024 | 4 | |
| 4 | 2023 | 4 | |
| 5 | 2002 | 48 | |
| 6 | The human p53 negative regulatory domain mediates inhibition of reporter gene transactivation in yeast lacking thioredoxin reductase. | 1999 | 32 |
| 7 | 1998 | 86 | |
| 8 | 1992 | 8 | |
| 9 | 1991 | 9 | |
| 10 | 1988 | 32 | |
| 11 | 1985 | 8 | |
| 12 | 1985 | 50 | |
| 13 | 1983 | 8 | |
| 14 | 1982 | 5 | |
| 15 | 1982 | 15 | |
| 16 | 1979 | 19 | |
| 17 | 1978 | 5 | |
| 18 | 1976 | 78 | |
| 19 | 1975 | 21 | |
| 20 | 1967 | 9 |
About George D. Pearson
George D. Pearson is a scholar working on Communication, Genetics, Molecular Biology, Metals and Alloys and Infectious Diseases, having authored 48 papers that have together received 1.2k indexed citations. Recurring topics across this work include Virus-based gene therapy research (20 papers), Viral Infectious Diseases and Gene Expression in Insects (10 papers), Bacteriophages and microbial interactions (8 papers), Viral gastroenteritis research and epidemiology (7 papers), Social Media and Politics (6 papers), CRISPR and Genetic Engineering (6 papers), RNA and protein synthesis mechanisms (4 papers) and RNA Interference and Gene Delivery (3 papers). The work is most often cited by research in Genetics (422 citations), Molecular Biology (828 citations), Communication (72 citations), Insect Science (91 citations) and Infectious Diseases (131 citations). George D. Pearson has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Gary F. Merrill, David H. Coombs, George F Rohrmann, Margot Pearson, Philip C. Hanawalt, Kai Wang, John W. Bodnar, H. Mark Engelking, J L Corden and Kevin Ahern. Their work appears in journals such as Virology, Proceedings of the National Academy of Sciences, Gene, Nucleic Acids Research and New Media & Society.
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.