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

  • July 2017: Our lab is hosting two Bruin in Genomics (B.I.G.) summer students.
  • June 2017: Soo Bin Kwon joins the lab.
  • April 2017: A new paper Systematic Epigenomic Analysis Reveals Chromatin States Associated with Melanoma Progression is published in Cell Reports. This has been a collaboration with researchers at MD Anderson and Pete is a first author on the paper.
  • March 2017: Jennifer Zou is selected to receive a NSF Graduate Research Fellowship.
  • February 2017: A new paper Cooperative Binding of Transcription Factors Orchestrates Reprogramming is published in Cell. The UCLA press release is here. This has been a collaboration with the Plath lab and Pete is a co-first author.
  • February 2017: Jason will be one of the organizers of the Regulatory Genomics Special Interest Group Meeting at ISMB 2017, which will now be integrated with the main ISMB meeting.
  • 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.

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    Upcoming Presentations

  • October 10, 2017: CHOP/UPenn Mid-Atlantic Bioinformatics Conference
  • November 10, 2017: CMU/Pitt Computational Biology Seminar Series