Peter Gee
Impact in
- Virology top 5%
- HIV Research and Treatment
Papers in
-
- CRISPR and Genetic Engineering 11
- Pluripotent Stem Cells Research 8
- RNA Interference and Gene Delivery 3
- Virology 6
- HIV Research and Treatment 6
- Co-authors
- Akitsu Hotta (10 shared papers)Huaigeng Xu (7 shared papers)Tommer Ravid (3 shared papers)Tzipora Goldkorn (3 shared papers)Noriko Sasakawa (5 shared papers)Yoshio Koyanagi (6 shared papers)Miyuki Ono (2 shared papers)Fumiyo Kitaoka (1 shared paper)
- Journals
- Journal of Biological Chemistry (3 papers)Journal of Virology (2 papers)Scientific Reports (1 paper)British Journal of Pharmacology (1 paper)The CRISPR Journal (1 paper)
- Partner nations
- JapanUnited StatesThailand
In The Last Decade
Peter Gee
27 papers receiving 1.4k citations
Peter Gee's Hit Papers
Peers
Comparison fields: 5 of 102
- Virology 186
- Business and International Management 38
- Aging 25
- Molecular Biology 961
- Immunology 269
Countries citing papers authored by Peter Gee
This map shows the geographic impact of Peter Gee'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 Peter Gee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Gee more than expected).
Fields of papers citing papers by Peter Gee
This network shows the impact of papers produced by Peter Gee. 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 Peter Gee. The network helps show where Peter Gee may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Gee, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Targeted Disruption of HLA Genes via CRISPR-Cas9 Generates iPSCs with Enhanced Immune Compatibility Hit paper breakdown → | 2019 | 411 |
| 2 | 2013 | 136 | |
| 3 | 2019 | 130 | |
| 4 | 2002 | 94 | |
| 5 | 2004 | 76 | |
| 6 | 2003 | 71 | |
| 7 | 2010 | 70 | |
| 8 | 2008 | 53 | |
| 9 | 2015 | 49 | |
| 10 | 2014 | 45 | |
| 11 | 2013 | 44 | |
| 12 | 2011 | 35 | |
| 13 | 2010 | 35 | |
| 14 | 2021 | 34 | |
| 15 | 2015 | 30 | |
| 16 | 2017 | 29 | |
| 17 | 2018 | 26 | |
| 18 | 2018 | 20 | |
| 19 | 2021 | 15 | |
| 20 | 2023 | 12 |
About Peter Gee
Peter Gee is a scholar working on Molecular Biology, Virology, Infectious Diseases, Aging and Oncology, having authored 27 papers that have together received 1.4k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (11 papers), Pluripotent Stem Cells Research (8 papers), HIV Research and Treatment (6 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers), RNA Interference and Gene Delivery (3 papers), Herpesvirus Infections and Treatments (3 papers), Mosquito-borne diseases and control (2 papers) and Neuroscience and Neural Engineering (2 papers). The work is most often cited by research in Virology (186 citations), Business and International Management (38 citations), Aging (25 citations), Molecular Biology (961 citations) and Immunology (269 citations). Peter Gee has collaborated with scholars based in Japan, United States and Thailand. Frequent co-authors include Akitsu Hotta, Huaigeng Xu, Tommer Ravid, Tzipora Goldkorn, Noriko Sasakawa, Yoshio Koyanagi, Miyuki Ono, Fumiyo Kitaoka, Masaki Nomura and Tomoko Takahashi. Their work appears in journals such as Journal of Biological Chemistry, Journal of Virology, Scientific Reports, British Journal of Pharmacology and The CRISPR Journal.
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.