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In recent years, new technologies have allowed researchers to perform multiple assays on the same set of patient samples. Typically these datasets contain observations of: genes (genomics), mRNA (transcriptomics), proteins (proteomics) and metabolites (metabolomics) and collectively are known as ‘Omics’ datasets. In this talk, I will discuss my research developing new methods in Bayesian and frequentist methodology for incorporating variable selection and dimension reduction for high dimensional Omics dataset.