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My research interests centre on the use of probabalistic (Bayesian) methods for extracting scientific knowledge from large, potentially complex data-sets.
Scientific data-sets often present us with particular challenges. For example, they may contain complex (unknown) structure, be noisy, inhomogeneous (missing some values), or even just very large. We might also want to include with our data other relevant prior knowledge that we have, for example from previous experiments or underlying physical principles. To get the most good science out of our data, we therefore must take all of these things into account. Bayesian methods allow us to do just that.
A Bayesian Clustering Analysis of Breast Cancer Gene Expression
as author at Poster Spotlights,