We are a computational biology lab within the Department of Biological Chemistry in the David Geffen School of Medicine and also part of the Computer Science Department, the Interdepartmental Bioinformatics Program, the Institute for Quantitative and Computational Biosciences, the Broad Stem Cell Research Center, the Jonsson Comprehensive Cancer Center, and the Molecular Biology Institute at UCLA.

The focus of the lab is on developing and applying machine learning methods for the analysis of high-throughput experimental data to address problems in epigenomics and gene regulation. Our research is often conducted in close collaboration with experimental groups. Please see the publications page to learn more about the lab's research.

We are recruiting new members, if interested please see the positions page.

Recent News

  • November 2016: Jason will be co-teaching COM SCI M225/BIOINFO M265/HUM GEN M265 'Computational Methods in Genomics' with Bogdan Pasaniuc in Winter 2016.
  • October 2016: A new paper Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions is published online in Nature Biotechnology. The paper describes Sharpr-MPRA which combines dense Massively Parallel Reporter Assay (MPRA) tiling with computational inference, and enabled high-resolution mapping of activating and repressive nucleotides within more than 15,000 predicted regulatory regions in two human cell types. The maps can be visualized here.
  • October 2016: The associated SHARPR software (Systematic High-resolution Activation and Repression Profiling with Reporter-tiling) with the Nature Biotechnology paper is publicly released.

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    Upcoming Presentations

  • January 28, 2017: Southern California Regional Conference on Systems Biology, UC Irvine