UAlberta Math-bio Seminar: Jay Newby

Abstract: We study stochastic motion of objects in micrometer-scale living systems: proteins in the nucleus, organelles in cells, and pathogens in mucus barriers. Phenomena such as self organization emerges from the behavior of single individuals. For example, the motion and interaction of proteins and RNA in the nucleus form liquid droplets which can form aggregates associated with neurodegenerative disease. We analyze microscopy videos using convolutional neural networks to begin the process of characterizing stochastic motion. We use stochastic models and state space models to track objects through time and infer properties of objects and their surroundings. Once validated with data, our stochastic models can be used to make predictions and elucidate mechanisms for physiological function. For example, we can calculate the distribution of first passage times for a pathogen to cross a mucus barrier. I will discuss examples that include tracking salmonella in GI mucus, genetically expressed proteins in the cell cytoplasm, and nuclear active transport in multinucleate fungal cells.