Gregory B. Ewing
Impact in
- Genetics top 5%
- Genetic diversity and population structure
- Evolution and Genetic Dynamics
- Genetic Mapping and Diversity in Plants and Animals
- Genetic and phenotypic traits in livestock
- Genetic Associations and Epidemiology
Papers in
-
- Statistical Methods and Inference 1
- Markov Chains and Monte Carlo Methods 1
- Genetics 3
- Evolution and Genetic Dynamics 3
- Genetic diversity and population structure 2
- Genetic and phenotypic traits in livestock 1
- Co-authors
- Joachim Hermisson (1 shared paper)Jeffrey D. Jensen (5 shared papers)Matthieu Foll (3 shared papers)Claudia Bank (2 shared papers)Heiko A. Schmidt (1 shared paper)Ingo Ebersberger (1 shared paper)Arndt von Haeseler (1 shared paper)Anna Ferrer-Admetlla (1 shared paper)
- Journals
- Molecular Ecology (2 papers)Trends in Genetics (1 paper)Statistical Applications in Genetics and Molecular Biology (1 paper)Frontiers in Genetics (1 paper)PLoS Genetics (1 paper)
- Partner nations
- SwitzerlandAustriaDenmark
In The Last Decade
Gregory B. Ewing
8 papers receiving 668 citations
Peers
Comparison fields: 5 of 78
- Genetics 515
- Ecological Modeling 16
- Molecular Biology 221
- Paleontology 24
- Ecology, Evolution, Behavior and Systematics 54
Countries citing papers authored by Gregory B. Ewing
This map shows the geographic impact of Gregory B. Ewing'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 Gregory B. Ewing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gregory B. Ewing more than expected).
Fields of papers citing papers by Gregory B. Ewing
This network shows the impact of papers produced by Gregory B. Ewing. 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 Gregory B. Ewing. The network helps show where Gregory B. Ewing may publish in the future.
Co-authors
The 25 scholars most cited alongside Gregory B. Ewing, 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 | 2010 | 268 | |
| 2 | 2015 | 131 | |
| 3 | 2014 | 101 | |
| 4 | 2014 | 93 | |
| 5 | 2008 | 51 | |
| 6 | 2015 | 18 | |
| 7 | 2015 | 8 | |
| 8 | 2017 | 7 | |
| 9 | 2007 | 0 |
About Gregory B. Ewing
Gregory B. Ewing is a scholar working on Statistics and Probability, Genetics, Demography, Philosophy and Artificial Intelligence, having authored 9 papers that have together received 677 indexed citations. Recurring topics across this work include Evolution and Genetic Dynamics (3 papers), Genomics and Phylogenetic Studies (2 papers), Genetic diversity and population structure (2 papers), Bayesian Methods and Mixture Models (2 papers), Genetic and phenotypic traits in livestock (1 paper), Influenza Virus Research Studies (1 paper), Statistical Methods and Inference (1 paper) and Markov Chains and Monte Carlo Methods (1 paper). The work is most often cited by research in Genetics (515 citations), Ecological Modeling (16 citations), Molecular Biology (221 citations), Paleontology (24 citations) and Ecology, Evolution, Behavior and Systematics (54 citations). Gregory B. Ewing has collaborated with scholars based in Switzerland, Austria and Denmark. Frequent co-authors include Joachim Hermisson, Jeffrey D. Jensen, Matthieu Foll, Claudia Bank, Heiko A. Schmidt, Ingo Ebersberger, Arndt von Haeseler, Anna Ferrer-Admetlla, Daniel N. A. Bolon and Jennifer P Wang. Their work appears in journals such as Molecular Ecology, Trends in Genetics, Statistical Applications in Genetics and Molecular Biology, Frontiers in Genetics and PLoS Genetics.
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.