Decoding Gene Regulation in 3D and in Single Cells

Sponsor(s): Computational Biology and Bioinformatics (CBB), Biomedical Engineering (BME), Biostatistics and Bioinformatics, Center for Advanced Genomic Technologies, Computer Science, Duke Center for Genomic and Computational Biology (GCB), Precision Genomics Collaboratory, School of Medicine (SOM), and University Program in Genetics & Genomics (UPGG)
The Leslie lab develops novel computational methods to study cellular biological systems from a global and data-driven perspective. They seek to exploit diverse, high-throughput functional and genomic data to understand the molecular networks underlying fundamental cellular processes, including regulation of transcription, pre-mRNA processing, signaling, and post-transcriptional gene silencing. Today's talk will present recent machine learning work to exploit single-cell chromatin accessibility and multiome data to decode gene regulation and cell dynamics.
Contact: Monica Franklin