Decoding Epigenetic Complexity: Modeling Gene Regulation with the Cistrome Data Browser

About this Class

The molecular mechanisms underlying many types of cancer involve aberrances in trans-acting factors and their binding to cis-regulatory elements to regulate gene expression. Techniques such as ChIP-seq, DNase-seq, and ATAC-seq are commonly used to profile the binding patterns of trans-factors and the chromatin landscape on a genome-wide scale, which are collectively referred to as "cistromes."

Integrating and analyzing cistrome data with gene expression profiles can provide valuable insights into the underlying mechanisms of cancer-related gene misregulation.
 
The Cistrome DB is a repository of annotated, processed, and quality-controlled publicly available cistrome data for human and mouse, designed to simplify cistrome data discovery, visualization, and analysis for experimental and computational biologists.
 
Discussed in the presentation will be:
•    recent Cistrome DB developments
•    description of methods for incorporating CistromeDB data in single cell ATAC-seq and RNA-seq multimodal analysis
•    introduction to new cistrome resources for deep neural network applications in regulatory genomics

For questions, contact Daoud Meerzaman or Kayla Strauss.