One of the defining features of cancerous cells is that they divide quickly. The composition of the human microbiome is also due to differences in how quickly microbes grow. How do we determine how fast cells are growing in their natural environment? Is there a way to take a ‘snapshot’ and turn it into a ‘growth rate’? This is the fundamental problem Dr. McCain is studying. He is using computational simulations, machine learning, and experiments with bacteria to determine the optimal way to use markers of gene expression to estimate these critical rates. This project will provide fundamental insights into the use of gene expression data to key processes like growth rate or metabolite secretion rate, both of which have implications for cancer biology. Dr. McCain received his MSc and PhD from Dalhousie University and his BSc from the University of Western Ontario.