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Peerj|October 1, 2019
EnContact: predicting enhancer-enhancer contacts using sequence-based deep learning modelMingxin Gan, Wenran Li, Rui JiangBiochemical Pharmacology|November 19, 2023
Strategies targeting IL-33/ST2 axis in the treatment of allergic diseasesWenran Li, Mengqi Liu, Ming ChuNucleic Acids Research|March 15, 2019
DeepTACT: predicting 3D chromatin contacts via bootstrapping deep learningWenran Li, Wing Hung Wong, Rui JiangACS Omega|March 25, 2024
Seq-RBPPred: Predicting RNA-Binding Proteins from SequenceYuyao Yan, Wenran Li, Sijia Wang, et al.Plos Computational Biology|July 1, 2026
DeepMethylation: A deep learning framework for tissue-specific DNA methylation prediction and functional variant annotationWenran Li, Shijia Yu, Yingyu Cheng, et al.Proceedings of the National Academy of Sciences of the United States of America|August 21, 2020
A method for scoring the cell type-specific impacts of noncoding variants in personal genomesWenran Li, Zhana Duren, Rui Jiang, et al.Molecular Biosystems|October 5, 2017
Gene co-opening network deciphers gene functional relationshipsWenran Li, Meng Wang, Jinghao Sun, et al.NAR Genomics and Bioinformatics|February 12, 2021
Associating divergent lncRNAs with target genes by integrating genome sequence, gene expression and chromatin accessibility dataYongcui Wang, Shilong Chen, Wenran Li, et al.BMC Systems Biology|September 28, 2017
Mimvec: a deep learning approach for analyzing the human phenomeMingxin Gan, Wenran Li, Wanwen Zeng, et al.BMC Bioinformatics|April 8, 2025
DeepMethyGene: a deep-learning model to predict gene expression using DNA methylationsYuyao Yan, Xinyi Chai, Jiajun Liu, et al.Pageof 3