Ucar Lab

Systems biology and immunology

Capturing the dynamics of epigenomic patterns is essential to understand how gene expression patterns are established and maintained in healthy human cells, and how they are disrupted by pathologies. However, discovering these patterns and interpreting their biological meaning is a significant computational challenge. We tackle this challenge by developing computational tools to mine and integrate diverse data sources (ChIA-PET, ATAC-seq, RNA-seq), since intricate regulatory interactions and diverse regulatory elements cannot be inferred from a single data type. We develop machine learning models or network mining algorithms to integrate and interpret genomics data from primary human cells under the light of data accumulated in public repositories.

Previous interest
Genomic signatures of immune system aging