Frank Park
Impact in
- Genetics top 2%
- Virus-based gene therapy research
- Nephrology top 5%
Papers in
-
- RNA Interference and Gene Delivery 11
- Renal and related cancers 6
- CRISPR and Genetic Engineering 6
- Genetics 28
- Virus-based gene therapy research 18
- Genetic and Kidney Cyst Diseases 9
- Co-authors
- Mark A. Kay (8 shared papers)Kazuo Ohashi (8 shared papers)Allen W. Cowley (8 shared papers)David L. Mattson (4 shared papers)Luigi Naldini (1 shared paper)Noriyuki Miyata (1 shared paper)Xiao Feng Li (1 shared paper)Feng Wu (1 shared paper)
- Journals
- American Journal of Physiology-Renal Physiology (9 papers)Physiological Genomics (6 papers)The FASEB Journal (5 papers)Molecular Therapy (4 papers)Hypertension (3 papers)
- Partner nations
- United StatesSouth KoreaJapan
In The Last Decade
Frank Park
84 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 119
- Genetics 807
- Nephrology 177
- Biochemistry 188
- Cardiology and Cardiovascular Medicine 411
- Molecular Biology 1.4k
Countries citing papers authored by Frank Park
This map shows the geographic impact of Frank Park'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 Frank Park with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Park more than expected).
Fields of papers citing papers by Frank Park
This network shows the impact of papers produced by Frank Park. 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 Frank Park. The network helps show where Frank Park may publish in the future.
Co-authors
The 25 scholars most cited alongside Frank Park, 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 91 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2000 | 285 | |
| 2 | 1999 | 227 | |
| 3 | 1999 | 163 | |
| 4 | 2007 | 124 | |
| 5 | 2000 | 123 | |
| 6 | 2017 | 102 | |
| 7 | 2001 | 100 | |
| 8 | 2013 | 84 | |
| 9 | 2011 | 80 | |
| 10 | 2001 | 80 | |
| 11 | 1997 | 71 | |
| 12 | 1997 | 59 | |
| 13 | 2008 | 48 | |
| 14 | 1998 | 44 | |
| 15 | 2009 | 43 | |
| 16 | 2010 | 42 | |
| 17 | 2011 | 42 | |
| 18 | 2013 | 42 | |
| 19 | 2002 | 42 | |
| 20 | 2000 | 41 |
About Frank Park
Frank Park is a scholar working on Molecular Biology, Genetics, Pathology and Forensic Medicine, Endocrinology, Diabetes and Metabolism and Physiology, having authored 91 papers that have together received 2.8k indexed citations. Recurring topics across this work include Virus-based gene therapy research (18 papers), RNA Interference and Gene Delivery (11 papers), Genetic and Kidney Cyst Diseases (9 papers), Renal and related cancers (6 papers), Cannabis and Cannabinoid Research (6 papers), Hormonal Regulation and Hypertension (6 papers), CRISPR and Genetic Engineering (6 papers) and Biomedical Research and Pathophysiology (5 papers). The work is most often cited by research in Genetics (807 citations), Nephrology (177 citations), Biochemistry (188 citations), Cardiology and Cardiovascular Medicine (411 citations) and Molecular Biology (1.4k citations). Frank Park has collaborated with scholars based in United States, South Korea and Japan. Frequent co-authors include Mark A. Kay, Kazuo Ohashi, Allen W. Cowley, David L. Mattson, Luigi Naldini, Noriyuki Miyata, Xiao Feng Li, Feng Wu, Quinn H. Hogan and Kevin R. Regner. Their work appears in journals such as American Journal of Physiology-Renal Physiology, Physiological Genomics, The FASEB Journal, Molecular Therapy and Hypertension.
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.