Detecting selection in genomes using deep learning

The application of deep learning, a branch of machine learning based on multi-layer neural networks, to biological data appears to be a revolutionary step to address complex questions, even in evolutionary biology.

In this seminar, I will first introduce some basic concepts of deep learning and how it can be applied to population genomic data for evolutionary inferences. I will then show some recent and ongoing work on using deep learning to identify signatures of balancing selection and adaptive introgression. I will finally outline some future research directions.

The seminar will be hosted using Zoom. A Google calendar invite featuring the Zoom link will be sent to Biology staff and students before the seminar date. For all enquiries please contact Biology DMT Hub.