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.

Lab News

  • Jan 18, 2024 -- EvoAug-TF preprint is out! Check it out here.
  • Jan 10, 2024 -- Aayush, PFF student and summer researcher from Half Hallow Hills High, is a Regeneron STS Scholar (Top 300)! Congrats!
  • Dec 7, 2023 -- Evan presents SQUID at CSHL's Genome Informatics meeting!
  • Nov 17, 2023 -- Evan's work on "Interpreting cis-regulatory mechanisms from genomic deep neural networks using surrogate models is now on bioRxiv!
  • Nov 10, 2023 -- Shush gets green light from thesis committee! Congrats!
  • Nov 8, 2023 -- Amber gets green light from thesis committee! Congrats!
  • Nov 6, 2023 -- Shush's submission on CREME is selected for Oral presentation at MLCB 2023! Chandana's and Amber's submission on unusual inits was accepted as a poster! Congrats!