Jonathan S. Dixon
Impact in
- Hepatology top 0.5%
- Hepatitis C virus research
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
Papers in
- Rheumatology 24
- Rheumatoid Arthritis Research and Therapies 22
- Hepatology 12
- Hepatitis C virus research 9
- Co-authors
- H. A. BirdDavid LipkinChoh Hao LiHon K. YuenDF GrayCha‐Ze LeeJoseph J.�Y. SungGeoffrey C. Farrell
- Journals
- Annals of the Rheumatic Diseases (11 papers)Journal of the American Chemical Society (8 papers)Clinical Rheumatology (7 papers)Lara D. Veeken (6 papers)Archives of Biochemistry and Biophysics (5 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Jonathan S. Dixon
110 papers receiving 5.5k citations
Hit Papers
Peers
Comparison fields: 5 of 165
- Hepatology 1.7k
- Computational Theory and Mathematics 974
- Epidemiology 1.8k
- Endocrinology, Diabetes and Metabolism 581
- Rheumatology 452
Countries citing papers authored by Jonathan S. Dixon
This map shows the geographic impact of Jonathan S. Dixon'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 Jonathan S. Dixon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan S. Dixon more than expected).
Fields of papers citing papers by Jonathan S. Dixon
This network shows the impact of papers produced by Jonathan S. Dixon. 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 Jonathan S. Dixon. The network helps show where Jonathan S. Dixon may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan S. Dixon, 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 | 2016 | 14 | |
| 2 | 2015 | 1 | |
| 3 | 2008 | 8 | |
| 4 | 2003 | 11 | |
| 5 | 2002 | 3 | |
| 6 | 1997 | 21 | |
| 7 | 1997 | 74 | |
| 8 | 1993 | 8 | |
| 9 | 1993 | 1 | |
| 10 | 1993 | 9 | |
| 11 | 1993 | 0 | |
| 12 | 1991 | 9 | |
| 13 | 1990 | 8 | |
| 14 | 1988 | 2 | |
| 15 | 1988 | 8 | |
| 16 | 1987 | 1 | |
| 17 | 1985 | 13 | |
| 18 | 1983 | 8 | |
| 19 | 1982 | 19 | |
| 20 | 1962 | 4 |
About Jonathan S. Dixon
Jonathan S. Dixon is a scholar working on Rheumatology, Hepatology, Endocrinology, Diabetes and Metabolism, Computational Theory and Mathematics and Gastroenterology, having authored 113 papers that have together received 6.0k indexed citations. Recurring topics across this work include Rheumatoid Arthritis Research and Therapies (22 papers), Growth Hormone and Insulin-like Growth Factors (14 papers), Computational Drug Discovery Methods (12 papers), Hepatitis C virus research (9 papers), Helicobacter pylori-related gastroenterology studies (8 papers), Chemical Synthesis and Analysis (7 papers), Monoclonal and Polyclonal Antibodies Research (7 papers) and Hepatitis B Virus Studies (6 papers). The work is most often cited by research in Hepatology (1.7k citations), Computational Theory and Mathematics (974 citations), Epidemiology (1.8k citations), Endocrinology, Diabetes and Metabolism (581 citations) and Rheumatology (452 citations). Jonathan S. Dixon has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include H. A. Bird, David Lipkin, Choh Hao Li, Hon K. Yuen, DF Gray, Cha‐Ze Lee, Joseph J.�Y. Sung, Geoffrey C. Farrell, Tawesak Tanwandee and Yun‐Fan Liaw. Their work appears in journals such as Annals of the Rheumatic Diseases, Journal of the American Chemical Society, Clinical Rheumatology, Lara D. Veeken and Archives of Biochemistry and Biophysics.
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.