Making sense of heterogeneity in gene expression data

Jessica Mar⁰
(0) University of Queensland

Abstract
Any model that we apply makes assumptions. But how often do we step back and question the validity of these assumptions? This talk includes studies from my group where a focus on the shape of gene expression distributions, specifically shape diversity, has revealed new insights into biology. Using topics from cancer and ageing, we have found that studying the shape of a gene’s expression distribution can represent a powerful means to modelling heterogeneity. Collectively, this work raises new questions and opportunities to understand how heterogeneity is gene expression contributes to regulation in genomics.