Stephen Forrest
Impact in
- Endocrinology top 10%
- Vibrio bacteria research studies
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- Yersinia bacterium, plague, ectoparasites research
- Forensic and Genetic Research
Papers in
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- Numerical Methods and Algorithms 1
- Polynomial and algebraic computation 1
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- Logic, programming, and type systems 2
- Co-authors
- David J. D. Earn (2 shared papers)Kirsten I. Bos (2 shared papers)Hendrik N. Poinar (2 shared papers)Sharon N. DeWitte (1 shared paper)Verena J. Schuenemann (1 shared paper)Sarah E. Schmedes (1 shared paper)Brian K. Coombes (1 shared paper)Alissa Mittnik (1 shared paper)
- Journals
- Proceedings of the National Academy of Sciences (1 paper)New England Journal of Medicine (1 paper)RWTH Publications (RWTH Aachen) (1 paper)Procedia Computer Science (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Stephen Forrest
6 papers receiving 253 citations
Peers
Comparison fields: 5 of 65
- Endocrinology 57
- Genetics 159
- Paleontology 27
- Archeology 34
- Molecular Medicine 15
Countries citing papers authored by Stephen Forrest
This map shows the geographic impact of Stephen Forrest'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 Stephen Forrest with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Forrest more than expected).
Fields of papers citing papers by Stephen Forrest
This network shows the impact of papers produced by Stephen Forrest. 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 Stephen Forrest. The network helps show where Stephen Forrest may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephen Forrest, 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 | 2011 | 147 | |
| 2 | 2014 | 106 | |
| 3 | 2013 | 4 | |
| 4 | 2016 | 2 | |
| 5 | Mining Maple Code for Contracts | 2006 | 2 |
| 6 | Integration of SMT-LIB Support into Maple. | 2017 | 2 |
About Stephen Forrest
Stephen Forrest is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Genetics, Computer Networks and Communications and Molecular Biology, having authored 6 papers that have together received 263 indexed citations. Recurring topics across this work include Yersinia bacterium, plague, ectoparasites research (2 papers), Logic, programming, and type systems (2 papers), Numerical Methods and Algorithms (1 paper), Advanced Database Systems and Queries (1 paper), Model-Driven Software Engineering Techniques (1 paper), Vibrio bacteria research studies (1 paper), Polynomial and algebraic computation (1 paper) and Systems Engineering Methodologies and Applications (1 paper). The work is most often cited by research in Endocrinology (57 citations), Genetics (159 citations), Paleontology (27 citations), Archeology (34 citations) and Molecular Medicine (15 citations). Stephen Forrest has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include David J. D. Earn, Kirsten I. Bos, Hendrik N. Poinar, Sharon N. DeWitte, Verena J. Schuenemann, Sarah E. Schmedes, Brian K. Coombes, Alissa Mittnik, William E. White and Johannes Krause. Their work appears in journals such as Proceedings of the National Academy of Sciences, New England Journal of Medicine, RWTH Publications (RWTH Aachen) and Procedia Computer Science.
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.