Project in Prairie
I will focus on the co-evolution of the immune system with viruses and tumours. An important aspect of this direction is combining large scale datasets (immune repertoires, single cell sequencing, neutralization assays) with dynamical models to predict future evolutionary trajectories. I will exploit phenotypic reproducibility and develop dynamic forecasting, optimization and control methods to predict individual and population level immune response. I will also combine data to build generative immune–pathogen interaction models.test
How can our adaptive immune system be prepared for the many pathogens we constantly encounter, even those that did not exist when we were born? A diverse ever-changing repertoire of receptor proteins on the surfaces of B and T cells interacts with pathogens, recognize them and initiates an immune response. The immune system is an example of how the interactions of many molecular and cellular elements result in the emergence of biological function – the recognition of pathogens. By combining statistical and machine learning based approaches to describe the formation of this distributed system, we can attempt identify its response to different pathogenic threats and propose predictive interventions.
