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.

Lazaridis, I. et al. (2024) “The Genetic Origin of the Indo-Europeans”, bioRxiv.

Falck, F. et al. (2024) “A framework for longitudinal latent factor modelling of treatment response in clinical trials with applications to Psoriatic Arthritis and Rheumatoid Arthritis”, Journal of Biomedical Informatics, 154.

Johnson, R. et al. (2024) “Investigating the dose-dependency of the midgut escape barrier using a mechanistic model of within-mosquito dengue virus population dynamics”, PLoS Pathogens, 20(4).

Creswell, R. et al. (2024) “Understanding the impact of numerical solvers on inference for differential equation models”, Journal of the Royal Society Interface, 21(212).

Gallagher, C. et al. (2024) “Epidemiological agent-based modelling software (Epiabm)”, Journal of Open Research Software, 12(1).

Stricker, M. et al. (2024) “Genome-wide classification of epigenetic activity reveals regions of enriched heritability in immune-related traits.”, Cell genomics, 4(3), p. 100508.

Goldberg, C. et al. (2024) “To do no harm — and the most good — with AI in health care”, Nature Medicine, 30(3), pp. 623–627.

Hampshire, A. et al. (2024) “Cognition and Memory after Covid-19 in a Large Community Sample”, New England Journal of Medicine, 390(9), pp. 806–818.

Spitschan, M. et al. (2024) “Power Analysis for Human Melatonin Suppression Experiments”, Clocks & Sleep, 6(1), pp. 114–128.

Liu, X. et al. (2024) “Directrices para presentación de informes de ensayos clínicos sobre intervenciones con inteligencia artificial: extensión CONSORT-AI”, BULL PAN AM HEALTH ORGAN, 48, p. e13.