Identifying target genes of enhancers is crucial for understanding their role in diseases. This study developed PEACOCK, a machine learning approach using experimentally validated enhancer-gene links and publicly available data to predict cell type-specific enhancer-gene regulatory relationships. The model was trained and validated across four cell lines, and the resulting scores were incorporated into the PEREGRINE database. These scores provide a quantitative framework for enhancer-gene regulatory prediction, facilitating downstream analyses and experimental validation.
Publisher
npj Systems Biology and Applications
Published On
Apr 03, 2023
Authors
Caitlin Mills, Crystal N. Marconett, Juan Pablo Lewinger, Huaiyu Mi
Tags
enhancer-gene relationships
machine learning
cancer research
bioinformatics
gene regulation
cell type-specific
PEREGRINE database
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