Ellis Patrick

Associate Professor Ellis Patrick is an applied statistician and bioinformatician in the Faculty of Science at the University of Sydney, holding the position of Associate Professor in the School of Mathematics and Statistics. He concurrently serves as a faculty member at the Westmead Institute for Medical Research and as the Cluster Lead of Bioinformatics in the Sydney Precision Data Science Centre. Patrick completed his PhD in statistical bioinformatics at the University of Sydney, with his thesis centered on the development of statistical methods for the analysis and interpretation of RNA-Seq data. Subsequently, he conducted postdoctoral research as a computational biologist, holding joint appointments at Brigham and Women’s Hospital, Harvard Medical School, and the Broad Institute of MIT and Harvard, where he investigated the molecular drivers of Alzheimer’s disease and multiple sclerosis using advanced statistical approaches.

Patrick's research program operates at the interface of statistics and biomedical data science, focusing on the creation, evaluation, and application of innovative bioinformatics tools to identify and interpret signals in large-scale, high-dimensional molecular and cellular datasets. His expertise enables the extraction of biological and clinical insights applicable to a range of human diseases, including infectious diseases, organ transplantation, cardiovascular disease, neurodegeneration, and cancer. Committed to open and reproducible science, he develops and shares widely adopted bioinformatics software packages. Key publications include 'Decoding the hallmarks of allograft dysfunction with a transcriptomic clock' in Nature Medicine (2024), 'Overcoming cohort heterogeneity for the prediction of subclinical cardiac allograft vasculopathy' in iScience (2023), 'MoleculeExperiment enables consistent infrastructure for molecule imaging data' in Bioinformatics (2023), and highly cited earlier works such as 'Clinical course, therapeutic responses and outcomes in relapsing MOG antibody-associated demyelination' (Annals of Neurology, 2018; 650 citations), 'A transcriptomic atlas of aged human microglia' (Nature Communications, 2018; 528 citations), 'A molecular network of the aging human brain provides insights into the pathology and cognitive decline of Alzheimer’s disease' (Nature Neuroscience, 2018; 526 citations), and 'An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome' (Nature Neuroscience, 2017; 507 citations). Patrick has obtained funding through Australian Research Council Discovery Projects and contributes to advancing precision data science methodologies.

Professional Email: ellis.patrick@sydney.edu.au