Professor
Chris Holmes
Professorial Fellow in Biostatistics in Genomics
Chair of Biostatistics at the departments of Statistics and the Nuffield Department of Medicine.
Affiliate Member of the Li Ka Shing Centre for Health Information and Discovery.
Scientific Director for the Health Programme at the Alan Turing Institute, London.
Department Website
Academic Background
I moved to Oxford from Imperial College London in February 2004. At Imperial College I studied for my doctorate in Bayesian statistics, investigating novel nonlinear pattern recognition methods. This was followed by a post-doctoral position and then a lectureship at Imperial. Previous to this I worked in industry for a number of years researching in scientific computing, developing techniques for real-time pattern recognition models in defence and SCADA (Supervisory Control and Data Acquisition) systems.
Research
I have a broad interest in the theory, methods and applications of statistics and statistical modelling.
My research explores the potential of computational statistics and statistical machine learning to assist in the medical and health sciences. In this respect I oversee a small research group working on probabilistic models and Bayesian decision analysis in complex biomedical data environments. This includes theoretical foundations, novel methodology, and “hands-on” study driven data science.
Research Interests
- Bayesian statistics
- Stochastic simulation
- Markov chain Monte Carlo
- Pattern recognition
- Spatial statistics
- Statistical genetics
- Statistical genomics
- Genetic epidemiology
Selected publications
- Watson J, Nieto-Barajas L and Holmes C, Characterizing variation of nonparametric random probability measures using the Kullback–Leibler divergence. Statistics 51 (3), pp. 558-571.
- Holmes C and S Walker, 2017, Assigning a value to a power likelihood in a general Bayesian model. Biometrika, 104 (2),pp. 497-403.
- de Angelis MH, Nicholson G, Selloum M, White J, Morgan H, Ramirez-Solis R, Sorg T, Wells S, Fuchs H, Fray M et al. 2015. Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics. Nat Genet, 47 (9), pp. 969-978.
- Taylor JC, Martin HC, Lise S, Broxholme J, Cazier JB, Rimmer A, Kanapin A, Lunter G, Fiddy S, Allan C et al. 2015. Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Nat Genet, 47 (7), pp. 717-726.
- Pinnick KE, Nicholson G, Manolopoulos KN, McQuaid SE, Valet P, Frayn KN, Denton N, Min JL, Zondervan KT, Fleckner J et al. 2014. Distinct developmental profile of lower-body adipose tissue defines resistance against obesity-associated metabolic complications. Diabetes, 63 (11), pp. 3785-3797.
- Nicholson G, Rantalainen M, Li J, Maher A, Malmodin D, Ahmadi K, Faber J, Barrett A, Min J, Rayner N, Toft H, Krestyaninova M, Viksna J, Guha Neogi S, Dumas M-E, Sarkans U, MolPAGE Consortium, Donnelly P, Illig T, Adamski J, Suhre K, Allen M, Zondervan K, Spector T, Nicholson J, Lindon J, Baunsgaard D, Holmes, E, McCarthy and Holmes C (2011) A genome-wide metabolic QTL analysis in Europeans implicates two loci shaped by recent positive selection. PLoS Genet 7.