Alexandra Gillett


Originally a Biostatistician, I developed an interest in high dimensional data analysis in biology. I am therefore undertaking a PhD in statistical genetics, focusing mathematical models of inheritance and risk prediction for disease. The development of such statistical methods are vital for the translation of research findings to the clinical arena.

In addition to the generous funding for a PhD that matched my interests, I was attracted to the Biomedical Research Centre (BRC) because of the unparalleled support offered to students. This ranges from monthly training sessions on a wide range of topics, to providing opportunities in which to present research and network.

2008-2009 MSc (Biostatistics), University of New South Wales
Graduated in 2007 BSc in Mathematics with Economics, 1st class, University of Sussex
Research statistician at:
2012-2013 Department of Women's Health, King's College London
2010-2012 Department of Statistics, Macquarie University
2009-2010 The Centre for the Mind, Sydney University

Modelling the genetic contribution to complex disease

Main areas of research: Statistical genetics, prediction modelling, genetic architecture of disease

This project aims to develop predictive models of disease which account for both rare and common genetic variation. Theoretical models of disease will be built in families and populations to determine likely patterns of genetic variants that combine to put individuals at high risk. To assist in achieving clinically useful levels of discrimination, genetic variants will be integrated with environmental and family history information in statistical risk prediction models. The large amount of information that will be made available to the modelling procedure, and the potential for complex interactions, will require the use and development of innovative statistical methodology.


Professor Cathryn Lewis and Professor Ammar Al-Chalabi

Research Team

Statistical Genetics Unit


Bioinformatics & statistics

Our bioinformatics and statistics research integrates complex rich clinical data from patient records with large datasets from other areas including genomics & brain imaging to better understand psychiatric disorders.

Training & development

We aim to attract outstanding candidates with a range of experience and offer a variety of training schemes and secondment opportunities, spanning all academic career pathways.
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