John Kim
Impact in
- Health Informatics top 0.2%
- Artificial Intelligence in Healthcare and Education
- Virology top 5%
- HIV Research and Treatment
Papers in
-
- HIV/AIDS Research and Interventions 10
- Tuberculosis Research and Epidemiology 9
- HIV/AIDS drug development and treatment 7
- Co-authors
- Gabriel D. Hayes (2 shared papers)George M. Church (2 shared papers)Gary Ruvkun (2 shared papers)Yonatan H. Grad (2 shared papers)Anna M. Krichevsky (1 shared paper)Kenneth S. Kosik (1 shared paper)Arya Rao (7 shared papers)Marc D. Succi (7 shared papers)
- Journals
- Radiographics (3 papers)Blood (3 papers)Vaccine (3 papers)Proceedings of the National Academy of Sciences (3 papers)Archives of Pharmacal Research (3 papers)
- Partner nations
- United StatesCanadaSouth Korea
In The Last Decade
John Kim
111 papers receiving 3.8k citations
John Kim's Hit Papers
Peers
Comparison fields: 5 of 163
- Health Informatics 360
- Virology 219
- Cancer Research 572
- Infectious Diseases 653
- Aging 57
Countries citing papers authored by John Kim
This map shows the geographic impact of John 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 John Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Kim more than expected).
Fields of papers citing papers by John Kim
This network shows the impact of papers produced by John 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 John Kim. The network helps show where John Kim may publish in the future.
Co-authors
The 25 scholars most cited alongside John 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 119 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Identification of many microRNAs that copurify with polyribosomes in mammalian neurons Hit paper breakdown → | 2003 | 470 |
| 2 | 2003 | 238 | |
| 3 | Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study Hit paper breakdown → | 2023 | 228 |
| 4 | 2023 | 189 | |
| 5 | 2011 | 171 | |
| 6 | 2006 | 171 | |
| 7 | Senolytic drugs, dasatinib and quercetin, attenuate adipose tissue inflammation, and ameliorate metabolic function in old age Hit paper breakdown → | 2023 | 162 |
| 8 | 1994 | 148 | |
| 9 | 2012 | 137 | |
| 10 | 2005 | 94 | |
| 11 | 2006 | 92 | |
| 12 | 2010 | 90 | |
| 13 | 1997 | 86 | |
| 14 | 1993 | 64 | |
| 15 | 2014 | 63 | |
| 16 | 2006 | 59 | |
| 17 | 2020 | 55 | |
| 18 | 2011 | 55 | |
| 19 | 2022 | 55 | |
| 20 | 2007 | 55 |
About John Kim
John Kim is a scholar working on Infectious Diseases, Molecular Biology, Epidemiology, Surgery and Immunology, having authored 119 papers that have together received 3.9k indexed citations. Recurring topics across this work include HIV/AIDS Research and Interventions (10 papers), Tuberculosis Research and Epidemiology (9 papers), HIV Research and Treatment (8 papers), Hepatitis C virus research (8 papers), HIV/AIDS drug development and treatment (7 papers), Hepatitis B Virus Studies (5 papers), HIV, Drug Use, Sexual Risk (5 papers) and Infectious Diseases and Tuberculosis (5 papers). The work is most often cited by research in Health Informatics (360 citations), Virology (219 citations), Cancer Research (572 citations), Infectious Diseases (653 citations) and Aging (57 citations). John Kim has collaborated with scholars based in United States, Canada and South Korea. Frequent co-authors include Gabriel D. Hayes, George M. Church, Gary Ruvkun, Yonatan H. Grad, Anna M. Krichevsky, Kenneth S. Kosik, Arya Rao, Marc D. Succi, Michael Pang and Winston Lie. Their work appears in journals such as Radiographics, Blood, Vaccine, Proceedings of the National Academy of Sciences and Archives of Pharmacal Research.
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.