ACME: pan-specific peptide-MHC class I binding prediction through attention-based deep neural networks. - Yan Hu; Ziqiang Wang; Hailin Hu 002; Fangping Wan; Lin Chen; Yuanpeng Xiong; Xiaoxia Wang; Dan Zhao 004; Weiren Huang; Jianyang Zeng 001 (Bioinform., 2019)

MONN: A Multi-objective Neural Network for Predicting Pairwise Non-covalent Interactions and Binding Affinities Between Compounds and Proteins. - Shuya Li; Fangping Wan; Hantao Shu; Tao Jiang 001; Dan Zhao 004; Jianyang Zeng 001 (RECOMB, 2020)

A novel machine learning framework for automated biomedical relation extraction from large-scale literature repositories. - Lixiang Hong; Jinjian Lin; Shuya Li; Fangping Wan; Hui Yang; Tao Jiang 001; Dan Zhao 004; Jianyang Zeng 001 (Nat. Mach. Intell., 2020)

Riboexp: an interpretable reinforcement learning framework for ribosome density modeling. - Hailin Hu 002; Xianggen Liu; An Xiao; Yangyang Li; Chengdong Zhang; Tao Jiang 001; Dan Zhao 004; Sen Song; Jianyang Zeng 001 (Briefings Bioinform., 2021)

Modeling gene regulatory networks using neural network architectures. - Hantao Shu; Jingtian Zhou; Qiuyu Lian; Han Li 018; Dan Zhao 004; Jianyang Zeng 001; Jianzhu Ma (Nat. Comput. Sci., 2021)

Full-length ribosome density prediction by a multi-input and multi-output model. - Tingzhong Tian; Shuya Li; Peng Lang; Dan Zhao 004; Jianyang Zeng 001 (PLoS Comput. Biol., 2021)

KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction. - Han Li 018; Dan Zhao 004; Jianyang Zeng 001 (KDD, 2022)

Boosting single-cell gene regulatory network reconstruction via bulk-cell transcriptomic data. - Hantao Shu; Fan Ding; Jingtian Zhou; Yexiang Xue; Dan Zhao 004; Jianyang Zeng 001; Jianzhu Ma (Briefings Bioinform., 2022)

Predicting the protein-ligand affinity from molecular dynamics trajectories. - Yaosen Min; Ye Wei; Peizhuo Wang; Nian Wu; Stefan Bauer; Shuxin Zheng; Yu Shi; Yingheng Wang; Dan Zhao 004; Ji Wu 002; Jianyang Zeng 001 (CoRR, 2022)

Characterizing the interaction conformation between T-cell receptors and epitopes with deep learning. - Xingang Peng; Yipin Lei; Peiyuan Feng; Lemei Jia; Jianzhu Ma; Dan Zhao 004; Jianyang Zeng 001 (Nat. Mac. Intell., 2023)

Improving comparative analyses of Hi-C data via contrastive self-supervised learning. - Han Li 018; Xuan He; Lawrence Kurowski; Ruotian Zhang; Dan Zhao 004; Jianyang Zeng 001 (Briefings Bioinform., 2023)

DeepRCI: predicting RNA-chromatin interactions via deep learning with multi-omics data. - Yuanpeng Xiong; Xuan He; Dan Zhao 004; Tao Jiang 001; Jianyang Zeng 001 (Quant. Biol., 2023)

MolSHAP: Interpreting Quantitative Structure-Activity Relationships Using Shapley Values of R-Groups. - Tingzhong Tian; Shuya Li; Meng Fang; Dan Zhao 004; Jianyang Zeng 001 (J. Chem. Inf. Model., 2024)

A probabilistic knowledge graph for target identification. - Chang Liu 082; Kaimin Xiao; Cuinan Yu; Yipin Lei; Kangbo Lyu; Tingzhong Tian; Dan Zhao 004; Fengfeng Zhou; Haidong Tang; Jianyang Zeng 001 (PLoS Comput. Biol., 2024)

Analyzing Large-Scale Single-Cell RNA-Seq Data Using Coreset. - Khalid Usman; Fangping Wan; Dan Zhao 004; Jian Peng 001; Jianyang Zeng 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2024)