Mark Beaumont

18.5k total citations · 5 hit papers
105 papers, 12.4k citations indexed

About

Mark Beaumont is a scholar working on Genetics, Ecology and Artificial Intelligence. According to data from OpenAlex, Mark Beaumont has authored 105 papers receiving a total of 12.4k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Genetics, 30 papers in Ecology and 17 papers in Artificial Intelligence. Recurrent topics in Mark Beaumont's work include Genetic diversity and population structure (58 papers), Genetic and phenotypic traits in livestock (24 papers) and Genetic Mapping and Diversity in Plants and Animals (19 papers). Mark Beaumont is often cited by papers focused on Genetic diversity and population structure (58 papers), Genetic and phenotypic traits in livestock (24 papers) and Genetic Mapping and Diversity in Plants and Animals (19 papers). Mark Beaumont collaborates with scholars based in United Kingdom, France and United States. Mark Beaumont's co-authors include David J. Balding, Wenyang Zhang, Jay F. Storz, Bruce Rannala, Gordon Luikart, Lounès Chikhi, Jean‐Michel Marin, Jean‐Marie Cornuet, Christian P. Robert and Arnaud Estoup and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Mark Beaumont

101 papers receiving 12.0k citations

Hit Papers

Approximate Bayesian Computation in Population Genetics 2002 2026 2010 2018 2002 2004 2010 2008 2019 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mark Beaumont United Kingdom 49 7.7k 3.4k 2.2k 1.7k 1.6k 105 12.4k
Olivier François France 42 5.3k 0.7× 2.2k 0.6× 1.9k 0.9× 1.5k 0.9× 1.2k 0.8× 143 9.9k
Jean‐Marie Cornuet France 54 11.1k 1.4× 3.9k 1.2× 2.6k 1.2× 5.5k 3.3× 2.6k 1.6× 80 15.1k
David J. Balding United Kingdom 58 9.3k 1.2× 1.2k 0.3× 4.7k 2.1× 638 0.4× 582 0.4× 169 15.0k
R. M. Cormack United Kingdom 27 2.9k 0.4× 4.6k 1.4× 1.2k 0.5× 1.6k 0.9× 2.7k 1.6× 55 11.5k
Korbinian Strimmer Germany 29 4.8k 0.6× 4.1k 1.2× 8.5k 3.9× 4.3k 2.6× 2.3k 1.4× 47 21.2k
Hidetoshi Shimodaira Japan 17 2.6k 0.3× 2.7k 0.8× 5.0k 2.3× 2.4k 1.4× 923 0.6× 53 11.2k
Oscar E. Gaggiotti United Kingdom 41 6.7k 0.9× 3.8k 1.1× 1.9k 0.9× 1.8k 1.1× 2.6k 1.6× 86 10.4k
A. W. F. Edwards United Kingdom 34 12.7k 1.7× 2.9k 0.9× 4.1k 1.9× 5.0k 3.0× 2.8k 1.7× 141 26.4k
Michaël G. B. Blum France 31 3.0k 0.4× 840 0.3× 1.1k 0.5× 562 0.3× 621 0.4× 60 5.3k
Bruce S. Weir United States 31 10.1k 1.3× 3.3k 1.0× 3.6k 1.6× 2.1k 1.3× 2.0k 1.2× 72 15.4k

Countries citing papers authored by Mark Beaumont

Since Specialization
Citations

This map shows the geographic impact of Mark Beaumont'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 Mark Beaumont with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Beaumont more than expected).

Fields of papers citing papers by Mark Beaumont

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark Beaumont. 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 Mark Beaumont. The network helps show where Mark Beaumont may publish in the future.

Co-authorship network of co-authors of Mark Beaumont

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Beaumont. A scholar is included among the top collaborators of Mark Beaumont based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mark Beaumont. Mark Beaumont is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lawson, Daniel J., et al.. (2024). How admixed captive breeding populations could be rescued using local ancestry information. Molecular Ecology. 34(19). e17349–e17349.
2.
Jamieson, Alexandra, Alberto Carmagnini, Isa‐Rita M. Russo, et al.. (2023). Genetic swamping of the critically endangered Scottish wildcat was recent and accelerated by disease. Current Biology. 33(21). 4761–4769.e5. 15 indexed citations
3.
Schiebelhut, Lauren M., Rena M. Schweizer, Ellie E. Armstrong, et al.. (2023). Genomics and conservation: Guidance from training to analyses and applications. Molecular Ecology Resources. 24(2). e13893–e13893. 8 indexed citations
4.
Beaumont, Mark, et al.. (2023). Estimating Temporally Variable Selection Intensity from Ancient DNA Data. Molecular Biology and Evolution. 40(3). 7 indexed citations
5.
Beaumont, Mark, et al.. (2021). Inferring the timing and strength of natural selection and gene migration in the evolution of chicken from ancient DNA data. Molecular Ecology Resources. 22(4). 1362–1379. 1 indexed citations
6.
8.
Macgregor, Callum J., Chris D. Thomas, David B. Roy, et al.. (2019). Climate-induced phenology shifts linked to range expansions in species with multiple reproductive cycles per year. Nature Communications. 10(1). 4455–4455. 334 indexed citations breakdown →
9.
Beaumont, Mark, et al.. (2017). Effects of the Ordering of Natural Selection and Population Regulation Mechanisms on Wright-Fisher Models. G3 Genes Genomes Genetics. 7(7). 2095–2106. 7 indexed citations
10.
Beaumont, Mark, et al.. (2015). Calibration and evaluation of individual-based models using Approximate Bayesian Computation. Ecological Modelling. 312. 182–190. 97 indexed citations
11.
Aeschbacher, Simon, Mark Beaumont, & Andreas Futschik. (2012). A Novel Approach for Choosing Summary Statistics in Approximate Bayesian Computation. Genetics. 192(3). 1027–1047. 64 indexed citations
12.
Sousa, Vítor C., Mark Beaumont, Pedro Fernandes, Maria M. Coelho, & Lounès Chikhi. (2011). Population divergence with or without admixture: selecting models using an ABC approach. Heredity. 108(5). 521–530. 42 indexed citations
13.
Antão, Tiago & Mark Beaumont. (2011). Mcheza: a workbench to detect selection using dominant markers. Bioinformatics. 27(12). 1717–1718. 81 indexed citations
14.
Nielsen, Rasmus & Mark Beaumont. (2009). Statistical inferences in phylogeography. Molecular Ecology. 18(6). 1034–1047. 202 indexed citations
15.
Beaumont, Mark. (2008). Joint determination of topology, divergence time, and immigration in population trees. Bristol Research (University of Bristol). 35(6). 22–4. 107 indexed citations
16.
Fagundes, Nelson J. R., Nicolas Ray, Mark Beaumont, et al.. (2007). Statistical evaluation of alternative models of human evolution. Proceedings of the National Academy of Sciences. 104(45). 17614–17619. 397 indexed citations
17.
Panchal, Mahesh & Mark Beaumont. (2007). THE AUTOMATION AND EVALUATION OF NESTED CLADE PHYLOGEOGRAPHIC ANALYSIS. Evolution. 61(6). 1466–1480. 134 indexed citations
18.
Kitchener, Andrew C., et al.. (2006). Geographical Variation in the Clouded Leopard, Neofelis nebulosa, Reveals Two Species. Current Biology. 16(23). 2377–2383. 51 indexed citations
19.
Cornuet, J. M. & Mark Beaumont. (2006). A note on the accuracy of PAC-likelihood inference with microsatellite data. Theoretical Population Biology. 71(1). 12–19. 12 indexed citations
20.
Butlin, Roger K., Mark Beaumont, & G. M. Hewitt. (1992). Selection for assortative mating between parapatric subspecies of grasshopper. Animal Behaviour. 43(6). 1045–1047. 1 indexed citations

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.

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