Using Deep Learning to find genetic causes of conditions such as Autism

We can now sequence the genome, but we still don’t know much about how to interpret it. Olga Troyanskaya, Professor of Bioinformatics and Functional Genomics at Princeton, discusses how deep learning is being used to work out what mutations mean and predict their effect, improving our understanding of conditions from autism to cancer to neurodegenerative diseases.

Olga Troyanskaya, Princeton University – Stanford Medicine Big Data | Precision Health 2016

Olga Troyanskaya is a Professor in the Lewis-Sigler Institute for Integrative Genomics and the Department of Computer Science at Princeton University and Deputy Director for Genomics at the Simons Center for Data Analysis at the Simons Foundation. Dr. Troyanskaya is a member of the Board of Directors of the International Society for Computational Biology and Associate Editor for Bioinformatics and PLOS Computational Biology. She received her Ph.D. from Stanford University and is a recipient of the Sloan Research Fellowship, the NSF CAREER award, the Howard Wentz faculty award, and the Blavatnik Finalist Award.

She has also been honored as one of the top young technology innovators by the MIT Technology Review and is the 2011 recipient of the Overton Prize from the International Society for Computational Biology and the 2014 Ira Herskowitz Award from the Genetic Society of America.

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