Peter Kim
Impact in
- Modeling and Simulation top 1%
- Mathematical Biology Tumor Growth
- Immunology top 5%
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
- T-cell and B-cell Immunology
Papers in
-
- Viral Infectious Diseases and Gene Expression in Insects 12
- Oncology 31
- CAR-T cell therapy research 17
- Co-authors
- Peter P. Lee (20 shared papers)Doron Levy (14 shared papers)Kristen Hawkes (11 shared papers)James E. Coxworth (3 shared papers)Adrianne L. Jenner (11 shared papers)Federico Frascoli (9 shared papers)Chae‐Ok Yun (8 shared papers)Gerard Sutton (2 shared papers)
- Journals
- Journal of Theoretical Biology (13 papers)Bulletin of Mathematical Biology (13 papers)Blood (5 papers)Clinical Infectious Diseases (5 papers)Cornea (5 papers)
- Partner nations
- United StatesAustraliaCanada
In The Last Decade
Peter Kim
204 papers receiving 4.1k citations
Peers
Comparison fields: 5 of 211
- Modeling and Simulation 273
- Immunology 686
- Hematology 272
- Transplantation 50
- Oncology 500
Countries citing papers authored by Peter Kim
This map shows the geographic impact of Peter Kim'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 Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Kim more than expected).
Fields of papers citing papers by Peter Kim
This network shows the impact of papers produced by Peter Kim. 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 Kim. The network helps show where Peter Kim may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Kim, 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 220 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2000 | 201 | |
| 2 | 2016 | 140 | |
| 3 | 2009 | 117 | |
| 4 | 2012 | 106 | |
| 5 | 2015 | 100 | |
| 6 | 1992 | 86 | |
| 7 | 2008 | 82 | |
| 8 | 2008 | 77 | |
| 9 | 1997 | 76 | |
| 10 | 2004 | 71 | |
| 11 | 2012 | 66 | |
| 12 | 2014 | 65 | |
| 13 | 2010 | 60 | |
| 14 | 2011 | 58 | |
| 15 | 1998 | 57 | |
| 16 | 2006 | 57 | |
| 17 | 2018 | 57 | |
| 18 | 2001 | 55 | |
| 19 | 1998 | 53 | |
| 20 | 2019 | 52 |
About Peter Kim
Peter Kim is a scholar working on Molecular Biology, Oncology, Genetics, Immunology and Radiology, Nuclear Medicine and Imaging, having authored 220 papers that have together received 4.3k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (19 papers), Virus-based gene therapy research (18 papers), CAR-T cell therapy research (17 papers), T-cell and B-cell Immunology (16 papers), Chronic Myeloid Leukemia Treatments (13 papers), Mathematical Biology Tumor Growth (13 papers), Evolutionary Psychology and Human Behavior (13 papers) and Viral Infectious Diseases and Gene Expression in Insects (12 papers). The work is most often cited by research in Modeling and Simulation (273 citations), Immunology (686 citations), Hematology (272 citations), Transplantation (50 citations) and Oncology (500 citations). Peter Kim has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Peter P. Lee, Doron Levy, Kristen Hawkes, James E. Coxworth, Adrianne L. Jenner, Federico Frascoli, Chae‐Ok Yun, Gerard Sutton, Sonia N. Yeung and Adelle C.F. Coster. Their work appears in journals such as Journal of Theoretical Biology, Bulletin of Mathematical Biology, Blood, Clinical Infectious Diseases and Cornea.
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.