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3 papers
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The paper introduces a computational method to identify modular regulatory programs from TF binding data, revealing combinatorial binding patterns and their cell-type-specific variations.
Haoyang Zeng, Matthew D. Edwards, Yuchun Guo, David K. Gifford
EnsembleExpr is an ensemble-based framework that accurately predicts eQTLs using MPRA data and outperforms existing methods in a CAGI challenge.
Haoyang Zeng, Tatsunori Hashimoto, Daniel D. Kang, David K. Gifford
GERV predicts regulatory variants affecting transcription factor binding by learning a k-mer based generative model from ChIP-seq and DNase-seq data, outperforming existing methods in SNP prediction.