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