Dan Andrews - JCSMR

Modern genetics has been transformed by the availability of public genome data at a population scale.  Yet, despite this revolution, we still only have a basic understanding of how to interpret the information encoded in genomes. My work focuses on data-driven approaches to better characterise both genotypic and phenotypic information, with the aim of bringing these together with novel computational methods.  Our data are derived from both model organisms and human clinical cohorts.  I will present recent progress in my lab that sheds new light on gene functional constraint and tolerance of proteins to amino acid substitutions caused by mutation. From the phenotype end, I will present new deep learning approaches we have developed that provide sensitive means to detect perturbations to cellular phenotype due to induced genetic variation. I will also discuss several applications of this work, especially in the context of the mouse model organism.

Dan Andrews leads a research group based between the John Curtin School of Medical Research and the ANU School of Computing.  His interests span genomics, bioinformatics, computational biology and increasingly involves data analytics and machine learning.  He is highly collaborative in multi-disciplinary partnerships.  Current collaborative activities include the nascent ANU/ACT Health Centre for Personalised Medicine and the Australian ImmunoGenomics Alliance.