Dr George Nicholson
I work with Chris Holmes and his research group on applied computational statistics focused on biomedical and genomic data. We're particularly interested in the development and application of statistical methods for replicable scientific discovery in biomedicine. The data we work on are typically complex and high-dimensional, comprising a combination of genetic, molecular and clinical data collected on cohorts, often with repeated measurements over time. Methodological areas of current interest include Bayesian sparse factor models, ensemble methods in multi-view learning, and identification of responder subgroups in clinical trials. I also enjoy the application of statistics more broadly, meeting regularly with researchers across the University as part of our Department's consultancy service.
Nicholson, G. and Holmes, C. (2017) A note on statistical repeatability and study design for high-throughput assays. Statistics in Medicine, 36, 790-798.
de Angelis, M., Nicholson, G., et al. (2015) Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics. Nature Genetics, doi:1038/ng/3360.
Nicholson, G., Rantalainen, M., et al. (2011) Human metabolic profiles are stably controlled by genetic and environmental variation. Molecular Systems Biology, 7, 525.
Nicholson, G., Rantalanien, M., et. al. (2011) A genome-wide metabolic QTL analysis in Europeans implicated two loci shaped by recent positive selection. PLoS Genetics, 7:9, e1002270.
Nicholson, G., Smith, A.V., et al. (2002) Assessing population differentiation and isolation from single nucleotide polymorphism data. Journal of the Royal Statistical Society, Series B (with discussion), 64, 695-715.