Explore a comprehensive lecture on applying sequence-based deep learning models to predict and explain regulatory functions from genomic DNA. Delve into the impact of cis-regulatory elements on cellular differentiation and disease-causing genetic variants. Examine recent advancements in adapting these models to study how natural genetic variation affects cellular function, and discover ongoing efforts to improve causal interpretation of non-coding genetic variation for accurate prediction of differential gene expression across individuals. Gain insights into how sequence-based deep learning approaches can uncover regulatory mechanisms and provide a powerful in-silico framework for probing the relationship between regulatory sequence and function.
Machine Learning Models of Differential Gene Expression
Overview
Syllabus
Machine learning models of differential gene expression
Taught by
Simons Institute
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