Efficient probabilistic inference and Bayesian non-parametrics with applications in phylogenetics and cancer genomics

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The fields of computational and statistical phylogenetics are concerned with the modelling and inference of evolutionary relationships. These fields have grown rapidly in recent years due to important advances in sequencing technologies. Many challenges, however, remain. One such example arises in the area of cancer phylogenetics, and relates to the characterization of evolutionary dynamics within cancer tumours. More specifically, the challenge arises from the need to characterize the evolution of individual cancer cells, where researchers are presented with mixtures of multiple sub-populations of cancer cells that have acquired different sets of mutations.