Machine Learning Models of Differential Gene Expression
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.