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Professor Mark Beaumont
Professor Mark Beaumont
BSc(Manc), PhD(Nott)
Professor of Statistics
Recent publications
- He, Z, Beaumont, M & Yu, F, 2017, ‘Effects of the ordering of natural selection and population regulation mechanisms on Wright-Fisher models’. G3, vol 7., pp. 2095-2106
- Vaart, Evd, Beaumont, MA, Johnston, ASA & Sibly, RM, 2015, ‘Calibration and evaluation of individual-based models using Approximate Bayesian Computation’. Ecological Modelling, vol 312., pp. 182-190
- North, TL & Beaumont, MA, 2015, ‘Complex trait architecture: The pleiotropic model revisited’. Scientific Reports, vol 5.
- Arenas, M, Lopes, JS, Beaumont, MA & Posada, D, 2015, ‘CodABC: A computational framework to coestimate recombination, substitution, and molecular adaptation rates by approximate bayesian computation’. Molecular Biology and Evolution, vol 32., pp. 1109-1112
- Lopes, JS, Arenas, M, Posada, D & Beaumont, MA, 2014, ‘Coestimation of recombination, substitution and molecular adaptation rates by approximate Bayesian computation’. Heredity, vol 112., pp. 255-264
- Vitalis, R, Gautier, M, Dawson, KJ & Beaumont, MA, 2014, ‘Detecting and measuring selection from gene frequency data’. Genetics, vol 196., pp. 799-817
- Razgour, ON, Juste, J, Ibanez, C, Kiefer, A, Rebelo, HEV, Puechmaille, S, Arlettaz, R, Burke, T, Dawson, D, Beaumont, MA & Jones, G, 2013, ‘The shaping of genetic variation in edge-of-range populations under past and future climate change.’. Ecology Letters, vol 16., pp. 1258?1266
- Aeschbacher, S, Futschik, A & Beaumont, MA, 2013, ‘Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates’. Molecular Ecology, vol 22., pp. 987-1002
- Nunes, VL, Beaumont, MA, Butlin, RK & Paulo, OS, 2012, ‘Challenges and pitfalls in the characterization of anonymous outlier AFLP markers in non-model species: lessons from an ocellated lizard genome scan’. Heredity, vol 109., pp. 340-348
- Sousa, VC, Beaumont, MA, Fernandes, P, Coelho, MM & Chikhi, L, 2012, ‘Population divergence with or without admixture: selecting models using an ABC approach’. Heredity, vol 108., pp. 521-530
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