John Fricks
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Health top 5%
- Vaccine Coverage and Hesitancy
Papers in
-
- Diffusion and Search Dynamics 4
-
- stochastic dynamics and bifurcation 5
- Statistical Mechanics and Entropy 3
- Co-authors
- Matthew J. Ferrari (3 shared papers)Emily Simons (1 shared paper)Peter M. Strebel (1 shared paper)Kathleen Wannemuehler (1 shared paper)Abhijeet Anand (1 shared paper)Anthony Burton (1 shared paper)William O. Hancock (8 shared papers)Timothy C. Elston (2 shared papers)
- Journals
- Journal of Theoretical Biology (3 papers)Journal of Statistical Computation and Simulation (2 papers)Biophysical Journal (2 papers)Bulletin of Mathematical Biology (2 papers)Biometrics (2 papers)
- Partner nations
- United StatesCyprusChina
In The Last Decade
John Fricks
26 papers receiving 478 citations
Peers
Comparison fields: 5 of 100
- Modeling and Simulation 99
- Health 154
- Epidemiology 213
- Structural Biology 8
- Cell Biology 76
Countries citing papers authored by John Fricks
This map shows the geographic impact of John Fricks'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 Fricks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Fricks more than expected).
Fields of papers citing papers by John Fricks
This network shows the impact of papers produced by John Fricks. 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 Fricks. The network helps show where John Fricks may publish in the future.
Co-authors
The 25 scholars most cited alongside John Fricks, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 224 | |
| 2 | 2009 | 45 | |
| 3 | 2010 | 28 | |
| 4 | 2011 | 28 | |
| 5 | 2019 | 22 | |
| 6 | 2019 | 17 | |
| 7 | 2020 | 16 | |
| 8 | 2016 | 15 | |
| 9 | 2015 | 13 | |
| 10 | 2019 | 12 | |
| 11 | 2005 | 12 | |
| 12 | 2011 | 11 | |
| 13 | 2012 | 11 | |
| 14 | 2019 | 10 | |
| 15 | 2010 | 9 | |
| 16 | 2020 | 7 | |
| 17 | 2006 | 6 | |
| 18 | 2013 | 5 | |
| 19 | 2010 | 4 | |
| 20 | 2012 | 2 |
About John Fricks
John Fricks is a scholar working on Molecular Biology, Statistical and Nonlinear Physics, Cell Biology, Mathematical Physics and Epidemiology, having authored 26 papers that have together received 503 indexed citations. Recurring topics across this work include Microtubule and mitosis dynamics (8 papers), stochastic dynamics and bifurcation (5 papers), Stochastic processes and statistical mechanics (5 papers), Diffusion and Search Dynamics (4 papers), Advanced Fluorescence Microscopy Techniques (3 papers), Statistical Mechanics and Entropy (3 papers), COVID-19 epidemiological studies (3 papers) and Virology and Viral Diseases (3 papers). The work is most often cited by research in Modeling and Simulation (99 citations), Health (154 citations), Epidemiology (213 citations), Structural Biology (8 citations) and Cell Biology (76 citations). John Fricks has collaborated with scholars based in United States, Cyprus and China. Frequent co-authors include Matthew J. Ferrari, Emily Simons, Peter M. Strebel, Kathleen Wannemuehler, Abhijeet Anand, Anthony Burton, William O. Hancock, Timothy C. Elston, M. Gregory Forest and Shi Chen. Their work appears in journals such as Journal of Theoretical Biology, Journal of Statistical Computation and Simulation, Biophysical Journal, Bulletin of Mathematical Biology and Biometrics.
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.