Post-doctoral research associate
George works in Chris Spencer's group in Oxford as a collaboration with MalariaGEN on the analysis of human genetic data. He explores the effects of demography and natural selection on the human genome. He is currently working with a large African dataset developing new models to identify regions of the genome that may have been altered in response to infectious disease. He is also interested in using genetic data to uncover novel inferences about our evolutionary past, and has helped developed models that characterise recent human admixture history.
Montinaro F, Busby, GBJ, Pascali VL, Myers S, Hellenthal G, Capelli C Unravelling the hidden ancestry of american admixed populations. (in press) Nature Communications.
Hellenthal G, Busby, GBJ, Band G, Wilson JF, Capelli C, Falush D, Myers S (2014) A genetic atlas of human admixture history. Science 343: 747–751
Busby, GBJ, Brisighelli F, Sánchez-Diz P, Ramos-Luis E, Martinez-Cadenas C, Thomas MG, Bradley DG, GusmãoL, Winney B, Bodmer W, Vennemann M, Coia V, Scarnicci F, Tofanelli S, Vona G, Ploski R, Vecchiotti C, Zemunik T, Rudan I, Karachanak S, Toncheva D, Anagnostou P, Ferri G, Rapone C, Hervig T, Moen T, Wilson JF, Capelli C (2012) The peopling of Europe and the cautionary tale of y chromosome lineage r-m269. Proceedings of the Royal Society B: Biological Sciences 279: 884 –892.
Flexible and cost-effective genomic surveillance ofP. falciparummalaria with targeted nanopore sequencing
de Cesare M. et al, (2023)
Integrating a Polygenic Risk Score for Coronary Artery Disease as a Risk-Enhancing Factor in the Pooled Cohort Equation: A Cost-Effectiveness Analysis Study.
Mujwara D. et al, (2022), J Am Heart Assoc, 11
Risk of Coronary Artery Disease Conferred by Low-Density Lipoprotein Cholesterol Depends on Polygenic Background.
Bolli A. et al, (2021), Circulation, 143, 1452 - 1454
Detection of B.1.351 SARS-CoV-2 Variant Strain - Zambia, December 2020.
Mwenda M. et al, (2021), MMWR. Morbidity and mortality weekly report, 70, 280 - 282
Genetic assessments of breast cancer risk that do not account for polygenic background are incomplete and lead to incorrect preventative strategies
Busby G. et al, (2021)