The Koo Lab studies gene regulation through a computational lens using data-driven machine learning solutions. Our approach develops deep learning methods to infer sequence-function relationships that underlie high-throughput functional genomics data. Through model interpretability, we aim to elucidate cis-regulatory mechanisms -- the complex coordination of sequence elements such as motifs -- with a broader aim of advancing precision medicine for complex diseases, including cancer. We are part of the Simons Center for Quantitative Biology and the NCI-designated Cancer Center at Cold Spring Harbor Laboratory.