Deciphering the transcriptional cis-regulatory code

The regulation of gene expression in response to developmental or environmental stimuli is a fundamental process in all mammalian cells. Our main goal is to elucidate the detailed mechanisms of transcriptional regulation, with a particular interest in the interplay between cis-regulatory elements and trans-acting factors, and their implications in gene transcription and cell fate decisions.

Major research directions:

1. Develop deep learning models and computational algorithms to analyze and interpret multi-omics data and regulatory sequences.
2. Characterize sequence determinants of regulatory elements, compatibility rules between promoters and enhancers, and cooperativity between transcription factors.
3. Decode gene regulatory network and their implications in cell fate decisions, such as cell differentiation, aging, and tumorigenesis.

To achieve these goals, we use a wide range of cutting-edge technologies, including deep learning, bioinformatics, genomics, CRISPR gene editing, high-throughput screening, and next generation sequencing techniques (such as STARR-Seq、Hi-C、ATAC-Seq、ChIP-Seq、RNA-Seq and so on).