Bioinformatics is an interdisciplinary field in which researchers develop tools to understand biological data. It uses multi-view datasets from different sources, such as microbiome and metagenomic data, to more accurately represent individuals. But the large-scale nature of these datasets-as well as differences between data types and the inability to generalize across biological systems-can make it difficult to realize the full potential of this information.
Dr. Sanjeena Dang, Canada Research Chair in Data Science and Analytics, has developed powerful statistical models to overcome these difficulties, and she and her research team are now using cutting-edge statistical algorithms to better understand biological systems. These models provide efficient, scalable techniques to identify important biological co-variates, characterize the microbiome along time-base lines (temporal trajectories), and explore the underlying biological mechanisms that drive these large-scale datasets.