MPS: David A. Garfield - Computational Approaches for Interpreting and Designing Cis-Regulatory Elements

Dr. Garfield has over 20 years of experience at the interface of experimental biology and bioinformatics, focusing onepigenetic regulation. His work includes developing computational methods for single-cell ATAC-seq analysis, machine learning approaches to predict the effects of regulatory mutations in the non-coding genome, and integrating computational tools into wet lab workflows. He previously led a junior research group at Humboldt University in Berlin and has held industry positions at Bayer and Genentech, where he initiated programs for synthetic regulatory elements and computational pipelines to empower experimental scientists.