Computational Methods for Modeling and Analyzing Epigenomic Data

Explore advanced computational approaches for modeling and analyzing epigenomic data in this 43-minute conference talk from the Computational Genomics Summer Institute. Delve into cutting-edge methodologies developed by Jason Ernst for understanding epigenetic modifications and their functional implications across diverse biological contexts. Learn about cross-species DNA methylation imputation techniques that enable comparative epigenomic analysis across mammalian species, and discover how to integrate epigenomic and functional data to characterize regulatory activity in human cell types. Examine gene-based modeling approaches for epigenomic data analysis and understand methods for universal genome annotation through large-scale integration of epigenomic datasets. Gain insights into computational strategies for learning conservation scores at the functional genomics level between human and mouse genomes, with practical applications for interpreting regulatory elements and their evolutionary significance.