Publications by Statistical Genetics and Epidemiology

Our research spans areas of statistical genetics, in particular the development of powerful statistical approaches to analyse genetic data, as well as studying infectious diseases.

Lyddon, S., Walker, S. and Holmes, C. (2018) “Nonparametric learning from Bayesian models with randomized objective functions”, in Advances in Neural Information Processing Systems, pp. 2071–2081.

Rukat, T., Holmes, C. and Yau, C. (2018) “Probabilistic Boolean Tensor Decomposition”, in Proceedings of Machine Learning Research, pp. 4413–4422.

Clements, M. et al. (2017) “Interpreting ambiguous ‘trace’ results in Schistosoma mansoni CCA Tests: estimating sensitivity and specificity of ambiguous results with no gold standard”, PLOS Neglected Tropical Diseases, 11(12), p. e0006102.

Rahmioglu, N. et al. (2017) “Variability of genome-wide DNA methylation and mRNA expression profiles in reproductive and endocrine disease related tissues”, Epigenetics, 12(10), pp. 897–908.

Altemose, N. et al. (2017) “A map of human PRDM9 binding provides evidence for novel behaviors of PRDM9 and other zinc-finger proteins in meiosis”, eLife, 6, p. e28383.

Daly, A. et al. (2017) “Comparing two sequential Monte Carlo samplers for exact and approximate Bayesian inference on biological models”, Interface, 14(134).

Gazal, S. et al. (2017) “Linkage disequilibrium dependent architecture of human complex traits reveals action of negative selection”, Nature Genetics, 49, pp. 1421–1427.

Lourenco, J. et al. (2017) “Epidemiological and ecological determinants of Zika virus transmission in an urban setting”, eLife, 6(eLife 2017).

Brunton, L. et al. (2017) “Assessing the effects of the first 2 years of industry‐led badger culling in England on the incidence of bovine tuberculosis in cattle in 2013–2015”, Ecology and Evolution, 7(18), pp. 7213–7230.

Drovandi, C. et al. (2017) “Principles of Experimental Design for Big Data Analysis”, Statistical Science, 32(3), pp. 385–404.