Dissecting Gene Regulation with Machine Learning: Discoveries and Challenges

Dissecting Gene Regulation with Machine Learning: Discoveries and Challenges

Statistics and Genomics Seminar
Jan 31, 2019, 04:00 PM - 05:00 PM | 1011 Evans Hall | Happening As Scheduled
Professor Katie Pollard, Department of Epidemiology and Biostatistics, UC San Francisco, Gladstone Institute, and Chan-Zuckerberg Biohub (Speaker)
Machine learning is a popular statistical approach in many fields, including genomics. We and others have used a variety of supervised machine-learning techniques to predict genes, regulatory elements, 3D interactions between regulatory elements and their target genes, and the effects of mutations on regulatory element function. I will highlight a few of these studies, emphasizing the strengths...