Computational Methods for Modeling and Analyzing Epigenomic Data

Explore computational methods for modeling and analyzing epigenomic data in this conference talk by Jason Ernst at the Computational Genomics Summer Institute 2024. Delve into cutting-edge approaches for understanding chromatin states, gene-based epigenomic modeling, and cross-species conservation of functional genomics. Learn about tools like ChromGene for gene-based epigenomic data modeling and ChromHMM for automating chromatin-state discovery. Discover techniques for large-scale imputation of epigenomic datasets and universal chromatin state annotation. Gain insights from related research papers on topics such as genome-wide human-mouse conservation scoring and systematic annotation of diverse human tissues using epigenomic data.

Jason Ernst | Computational Methods for Modeling and Analyzing Epigenomic Data | CGSI 2024