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

  • Apr 8, 2024 -- SQUID manuscript is accepted in Nature Machine Intelligence! Congrats Evan!
  • Apr 4, 2024 -- Pretty is awarded the NSF Graduate Research Fellowship! Congrats!
  • Mar 8, 2024 -- EvoAug-TF is published in Bioinformatics here.
  • Mar 4, 2024 -- Amber's work on "Evaluating the representational power of pre-trained DNA language models for regulatory genomics" in on bioRxiv!
  • 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!