David Balding, Professor of Statistical Genomics and MIG Director, University of Melbourne
Welcome to my webpage.
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.
- 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:
• Population Genetics