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Nucleic Acids Research|March 24, 2017
Predicting the impact of non-coding variants on DNA methylationHaoyang Zeng, David K GiffordBioinformatics (Oxford, England)|September 13, 2019
DeepLigand: accurate prediction of MHC class I ligands using peptide embeddingHaoyang Zeng, David K GiffordCell Systems|June 10, 2019
Quantification of Uncertainty in Peptide-MHC Binding Prediction Improves High-Affinity Peptide Selection for Therapeutic DesignHaoyang Zeng, David K GiffordBMC Bioinformatics|July 21, 2019
Visualizing complex feature interactions and feature sharing in genomic deep neural networksGe Liu, Haoyang Zeng, David K GiffordBioinformatics (Oxford, England)|October 19, 2015
GERV: a statistical method for generative evaluation of regulatory variants for transcription factor bindingHaoyang Zeng, Tatsunori Hashimoto, Daniel D Kang, et al.Human Mutation|February 23, 2017
Accurate eQTL prioritization with an ensemble-based frameworkHaoyang Zeng, Matthew D Edwards, Yuchun Guo, et al.Bioinformatics (Oxford, England)|June 17, 2016
Convolutional neural network architectures for predicting DNA-protein bindingHaoyang Zeng, Matthew D Edwards, Ge Liu, et al.Bioinformatics (Oxford, England)|March 11, 2021
Machine learning optimization of peptides for presentation by class II MHCsZheng Dai, Brooke D Huisman, Haoyang Zeng, et al.Bioinformatics (Oxford, England)|November 29, 2019
Antibody complementarity determining region design using high-capacity machine learningGe Liu, Haoyang Zeng, Jonas Mueller, et al.Genome Research|July 27, 2016
A synergistic DNA logic predicts genome-wide chromatin accessibilityTatsunori Hashimoto, Richard I Sherwood, Daniel D Kang, et al.Pageof 11