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Mining big data for answers to CWD

After years of sequencing the genome of many organisms, science is drowning in data yet often unable to reach out and touch the valuable bits of information that will turn that data into knowledge. Deep learning and artificial intelligence are ready to save important insights from disappearing into an ocean of genomics data.

Paul Stothard is an Associate Professor at the University of Alberta's Faculty of Agricultural, Life and Environmental Sciences and he specializes in the analysis of DNA sequence information. He has been involved in many of Genome Alberta's funded projects and his latest connection is with our project on Chronic Wasting Disease. His role on the project is to sort through the data, tease out the true results, and ultimately help the team use gene expression techniques to  help identify animals with CWD. Potentially that means taking a blood sample and coming up with a diagnosis.
The researchers are only about a year and a half into the 4-year project so there is still a lot of work left to be done if they are to help stop the spread of the fatal disease.
Freelance broadcaster Don Hill talked with Paul Stothard about the data analysis and the potential for deep learning to address the challenges.

Mining big data for answers to CWD

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