Maynard Thompson
Impact in
- Modeling and Simulation top 2%
- Mathematical Biology Tumor Growth
- Fractional Differential Equations Solutions
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- Mathematical and Theoretical Epidemiology and Ecology Models
Papers in
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- COVID-19 epidemiological studies 3
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- Advanced Mathematical Theories and Applications 1
- Co-authors
- H. I. Freedman (1 shared paper)Daniel P. Mäki (2 shared papers)Ronald W. Shonkwiler (4 shared papers)Richard M. Shiffrin (1 shared paper)John D. Emerson (1 shared paper)
- Journals
- Proceedings of the American Mathematical Society (2 papers)Bulletin of Mathematical Biology (2 papers)Duke Mathematical Journal (1 paper)Information Sciences (1 paper)Mathematical Biosciences (1 paper)
- Partner nations
- United States
In The Last Decade
Maynard Thompson
12 papers receiving 465 citations
Maynard Thompson's Hit Papers
Peers
Comparison fields: 5 of 83
- Modeling and Simulation 140
- Public Health, Environmental and Occupational Health 382
- Genetics 250
- Geometry and Topology 69
- Applied Mathematics 63
Countries citing papers authored by Maynard Thompson
This map shows the geographic impact of Maynard Thompson'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 Maynard Thompson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maynard Thompson more than expected).
Fields of papers citing papers by Maynard Thompson
This network shows the impact of papers produced by Maynard Thompson. 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 Maynard Thompson. The network helps show where Maynard Thompson may publish in the future.
Co-authors
The 5 scholars most cited alongside Maynard Thompson, 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 | Deterministic Mathematical Models in Population Ecology. Hit paper breakdown → | 1982 | 426 |
| 2 | Mathematical Modeling and Computer Simulation | 2005 | 19 |
| 3 | 1964 | 9 | |
| 4 | 1988 | 8 | |
| 5 | 1982 | 5 | |
| 6 | 1978 | 5 | |
| 7 | 1982 | 5 | |
| 8 | 1986 | 3 | |
| 9 | 1979 | 3 | |
| 10 | 1981 | 1 | |
| 11 | 1969 | 1 | |
| 12 | 1986 | 1 | |
| 13 | 1969 | 0 |
About Maynard Thompson
Maynard Thompson is a scholar working on Modeling and Simulation, Statistical and Nonlinear Physics, Computational Mechanics, Public Health, Environmental and Occupational Health and Statistics and Probability, having authored 13 papers that have together received 486 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (3 papers), Mathematical and Theoretical Epidemiology and Ecology Models (2 papers), Advanced Numerical Analysis Techniques (2 papers), Iterative Methods for Nonlinear Equations (1 paper), Stochastic processes and statistical mechanics (1 paper), Toxoplasma gondii Research Studies (1 paper), Bayesian Modeling and Causal Inference (1 paper) and Advanced Mathematical Theories and Applications (1 paper). The work is most often cited by research in Modeling and Simulation (140 citations), Public Health, Environmental and Occupational Health (382 citations), Genetics (250 citations), Geometry and Topology (69 citations) and Applied Mathematics (63 citations). Maynard Thompson has collaborated with scholars based in United States. Frequent co-authors include H. I. Freedman, Daniel P. Mäki, Ronald W. Shonkwiler, Richard M. Shiffrin and John D. Emerson. Their work appears in journals such as Proceedings of the American Mathematical Society, Bulletin of Mathematical Biology, Duke Mathematical Journal, Information Sciences and Mathematical Biosciences.
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.