Join Dr. Tony Kess, Researcher at Fisheries and Oceans Canada based at the Bedford Institute of Oceanography, to learn about the project “Polygenic architecture of life history divergence in North American Atlantic Salmon”. Simply put, the team has been using machine learning to better understand the genetic basis of traits important for the life cycle of the declining population of North American Atlantic Salmon. For this session, Tony will explain why DFO has been exploring the genetic basis of salmon life history, and describe how understanding variation in this adaptive genetic variation can support the management and potential restoration of this critical species. For those interested in some technical aspects, Tony will also touch on statistical and machine learning tools used in population genetics, including principal component analyses, genome-wide association, and random forest and out of bag sampling.

Who should attend:

• Those who are interested in understanding machine learning use in genetic analysis
• Those with marine conservation focus

Dr. Tony Kess holds a PhD in Integrative Biology from the University of Guelph, completed in 2017. After an NSERC Visiting Postdoctoral Fellowship at the Bedford of Institute of Oceanography, he is currently a Researcher with the Department of Fishers and Oceans.

DeepSense Discovery Sessions provide industry partners and students from any academic institution with an interest in data science and the ocean sector to learn more about the ocean economy, ocean data, participate in challenges presented by ocean-related companies and explore the potential of ocean data. Students (and non-students) are welcome to attend any and all DeepSense sessions. DeepSense Discovery Sessions are held online and posted on the DeepSense YouTube page . If you have a topic you want to learn more about reach out info@deepsense.ca.