David Balding's home page

Statistical Genomics

David Balding, Professor of Statistical Genomics and MIG Director, University of Melbourne

djbhandsWelcome to my webpage.

I am Director of Melbourne Integrative Genomics and R@MAP (Research @ Melbourne Accelerator Program) Professor of Statistical Genomics (since Nov 2014), based jointly in the School of BioSciences and the School of Mathematics & Statistics.

 

I also have an affiliation with the UCL Genetics Institute in London, where I was based full time from 2009 to 2014.

 

My educational background is in maths (D Phil Mathematics, Oxford 1990) and since then I have worked to develop and apply mathematical/statistical/computational methods and ideas in genetics and genomics.

Some of the main themes of my research are:
  • mathematical modelling of
    • ancestry and relatedness,
    • demographic history of populations,
    • evolutionary processes such as mechanisms of selection;
  • statistical methods for identifying sources of biological material in forensic science (identification of individual or tissue);
  • measures of relatedness among two or more individuals and the role of relatedness in genomics analyses, including association studies;
  • heritability and the genomic architecture of complex traits;
  • predicting phenotypes from genotype and other data;
  • analysis of other omics data (transcriptome, methylome, etc) in conjunction with genomics data.

Much of the above is informed by the coalescent-with-recombination model of population genetics. Performing statistical inference for large datasets under this model remains one of the major open problems in statistical genomics. Other statistical tools include mixed model (or penalised/shrinkage) regression for large numbers of predictors (p >> n) and various multivariate statistics techniques.

I have worked with collaborators in many different fields: forensic science, crop research, ancient DNA, pharmaceutical companies and diseases of humans, animals and plants. Much of this work involves stochastic modelling based on data generated by the collaborative partner or from public databases.

Some key words:

• Computational statistics
• Epidemiology and Biostatistics
• Evaluation of forensic DNA profiles
• Evolutionary Genetics
• Genetic Epidemiology
• Population Genetics
Please see the menu at the top right of the page for links to further details of my research and how to join my group as an MSc or PhD student.