Professor Sylvia Richardson

CBE, PhD (Nottingham) DDÉ TAT (Paris Sud-Orsay)

Bye-Fellow
MRC Research Professor of Biostatistics and Director of the Medical Research Council Biostatistics Unit, Cambridge

Biography

My work has contributed to progress in epidemiological understanding and has covered spatial modelling and disease mapping, mixture and clustering models as well as integrative analysis of observational data from different sources. My recent research has focussed on modelling and analysis of large data problems such as those arising in genomics.

Full CV Prof S Richardson

Selected Papers

• J Pettit , R Tomer , K Achim, S Richardson, L Azizi , J Marioni (2014)
  Identifying Cell Types from Spatially Referenced Single-Cell Expression Datasets. PLoS Computational Biology
  PLoS Computational Biology Volume 9 - Issue 10: E1003824
• G Papageorgiou, S Richardson & N Best (2014)
  Bayesian nonparametric models for spatially indexed data of mixed type
  Journal of the Royal Statistical Society Series B (2014) : First published online: 13 Dec 2014
• PJ Newcombe, H Raza Ali, FM Blows,E Provenzano, PD Pharoah, C Caldas and S Richardson (4 September 2014)
  Weibull regression with Bayesian variable selection to identify prognostic tumour markers of breast cancer survival
  Stat Methods Med Res 0(0) : 1–23
• D Hastie, S Liverani & S Richardson (2014 )
  Sampling from Dirchlet process mixture models with unknown concentration parameter: mixing issues in large data implementations
  Statistics and Computing Published online: 3 May 2014:
• L Bottolo, M Chadeau-Hyam, coll. & S Richardson (2013)
  GUESS-ing polygenic associations with multiple phenotypes using a GPU-based Evolutionary Stochastic Search algorithm
  Journal of Computational Biology Volume 9 - Issue 8 : E1003657
• P Kirk, A Witkover, CRM Bangham, S Richardson, AM Lewin & MPH Stumpf (2013)
  Balancing the Robustness and Predictive Performance of Biomarkers
  Journal of Computational Biology Volume: 20 Issue 12: : 1-11
• S Geneletti, N Best, MB Toledano, P Elliott & S Richardson (10 July 2013)
  Uncovering selection bias in case-control studies using Bayesian post-stratification
  Wiley Online Library Volume 32 - Issue 15: 663–674
• M Papathomas, J Molitor; C Hoggart; D Hastie & S Richardson. (September 2012)
  Exploring Data From Genetic Association Studies Using Bayesian Variable Selection and the Dirichlet Process: Application to Searching for Gene × Gene Patterns
  Genetic Epidemiology Volume 36, Issue 6, : 663–674
• Bottolo, L., Petretto, E., Blankenberg, S., Cambien, F., Cook, S. A., Tiret, L. & Richardson, S. (2011)
  Bayesian detection of expression quantitative trait loci hot spots.
  Genetics 189: 1449-1459
• Jackson, C., Best, N. & Richardson, S. (2009)
  Bayesian graphical models for regression on multiple datasets with different variables.
  Biostatistics 10: 335-351
• Molitor, J. T., Papathomas, M., Jerrett, M. & Richardson, S. (2010)
  Bayesian Profile Regression with an Application to the National Survey of Children’s Health.
  Biostatistics 11: 484-498
• Petretto, E., Bottolo, L., Langley, S. R., Heining, M., McDermott-Roe, C., Sarwar, R., Pravenec, M., Hübner, N., Aitman, T. J., Cook, S. A. & Richardson, S. (2010)
  New Insights into the Genetic Control of Gene Expression using a Bayesian Multi-tissue Approach.
  PLoS Computational Biology 6: e1000737
• Ratmann, O., Andrieu, C., Wiuf, C. & Richardson, S. (2009)
  Model criticism based on likelihood-free inference, with an application to protein network evolution.
  Proceedings of the National Academy of Sciences USA 106: 10576-10581

• Publications list Prof S Richardson

Research

I have worked extensively in many areas of biostatistics research and have made extensive contributions to the statistical modelling of complex biomedical data, in particular from a Bayesian perspective.

Email

• sylvia.richardson@mrc-bsu.cam.ac.uk

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