Supervised learning of enhancer-promoter specificity based on genome-wide perturbation studies highlights areas for improvement in learning.

Journal: Bioinformatics (Oxford, England)
PMID: 38870532

Abstract

MOTIVATION: Understanding the rules that govern enhancer-driven transcription remains a central unsolved problem in genomics. Now with multiple massively parallel enhancer perturbation assays published, there are enough data that we can utilize to learn to predict enhancer-promoter (EP) relationships in a data-driven manner.

Authors

  • Dylan Barth
    School of Life Sciences, University of Nevada, Las Vegas, NV 89154, United States.
  • Richard Van
    Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States.
  • Jonathan Cardwell
    Department of Medicine, University of Colorado School of Medicine, Denver, CO 80045, United States.
  • Mira V Han
    Nevada Institute of Personalized Medicine, University of Nevada, Las Vegas, 4505 Maryland Parkway, Las Vegas, NV, 89154-4009, USA.

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