Detecting microarray data supported microRNA-mRNA interactions. - Hui Liu 026; Shuigeng Zhou; Jihong Guan (Int. J. Data Min. Bioinform., 2010)

Effectively predicting protein functions by collective classification - An extended abstract. - Wei Xiong; Hui Liu 026; Jihong Guan; Shuigeng Zhou (BIBM Workshops, 2012)

Protein function prediction by collective classification with explicit and implicit edges in protein-protein interaction networks. - Wei Xiong; Hui Liu 026; Jihong Guan; Shuigeng Zhou (BMC Bioinform., 2013)

Identifying Mammalian MicroRNA Targets Based on Supervised Distance Metric Learning. - Hui Liu 026; Shuigeng Zhou; Jihong Guan (IEEE J. Biomed. Health Informatics, 2013)

A comparative evaluation on prediction methods of nucleosome positioning. - Hui Liu 026; Ruichang Zhang; Wei Xiong; Jihong Guan; Ziheng Zhuang; Shuigeng Zhou (Briefings Bioinform., 2014)

The centrality of cancer proteins in human protein-protein interaction network: a revisit. - Wei Xiong; Luyu Xie; Shuigeng Zhou; Hui Liu 026; Jihong Guan (Int. J. Comput. Biol. Drug Des., 2014)

Improving compound-protein interaction prediction by building up highly credible negative samples. - Hui Liu 026; Jianjiang Sun; Jihong Guan; Jie Zheng 002; Shuigeng Zhou (Bioinform., 2015)

Inferring new indications for approved drugs via random walk on drug-disease heterogenous networks. - Hui Liu 026; Yinglong Song; Jihong Guan; Libo Luo; Ziheng Zhuang (BMC Bioinform., 2016)

Screening lifespan-extending drugs in Caenorhabditis elegans via label propagation on drug-protein networks. - Hui Liu 026; Mengmeng Guo; Ting Xue; Jihong Guan; Libo Luo; Ziheng Zhuang (BMC Syst. Biol., 2016)

Generalized logical model based on network topology to capture the dynamical trends of cellular signaling pathways. - Fan Zhang 089; Haoting Chen; Li Na Zhao; Hui Liu 026; Teresa M. Przytycka; Jie Zheng 002 (BMC Syst. Biol., 2016)

SynLethDB: synthetic lethality database toward discovery of selective and sensitive anticancer drug targets. - Jing Guo; Hui Liu 026; Jie Zheng 002 (Nucleic Acids Res., 2016)

Selecting high-quality negative samples for effectively predicting protein-RNA interactions. - Zhanzhan Cheng; Kai Huang 011; Yang Wang 100; Hui Liu 026; Jihong Guan; Shuigeng Zhou (BMC Syst. Biol., 2017)

A new hybrid method for learning bayesian networks: Separation and reunion. - Hui Liu 026; Shuigeng Zhou; Wai Lam; Jihong Guan (Knowl. Based Syst., 2017)

XPredRBR: Accurate and Fast Prediction of RNA-Binding Residues in Proteins Using eXtreme Gradient Boosting. - Lei Deng 002; Zuojin Dong; Hui Liu 026 (ISBRA, 2018)

PDRLGB: precise DNA-binding residue prediction using a light gradient boosting machine. - Lei Deng 002; Juan Pan; Xiaojie Xu; Wenyi Yang; Chuyao Liu; Hui Liu 026 (BMC Bioinform., 2018)

Effectively Identifying Compound-Protein Interactions by Learning from Positive and Unlabeled Examples. - Zhanzhan Cheng; Shuigeng Zhou; Yang Wang 100; Hui Liu 026; Jihong Guan; Yi-Ping Phoebe Chen (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

A deep neural network approach using distributed representations of RNA sequence and structure for identifying binding site of RNA-binding proteins. - Lei Deng 002; Youzhi Liu; Yechuan Shi; Hui Liu 026 (BIBM, 2019)

D2VCB: A Hybrid Deep Neural Network for the Prediction of in-vivo Protein-DNA Binding from Combined DNA Sequence. - Lei Deng 002; Hui Wu; Hui Liu 026 (BIBM, 2019)

MADOKA: an ultra-fast approach for large-scale protein structure similarity searching. - Lei Deng 002; Guolun Zhong; Chenzhe Liu; Judong Luo; Hui Liu 026 (BMC Bioinform., 2019)

Predicting effective drug combinations using gradient tree boosting based on features extracted from drug-protein heterogeneous network. - Hui Liu 026; Wenhao Zhang; Lixia Nie; Xiancheng Ding; Judong Luo; Ling Zou 002 (BMC Bioinform., 2019)

Predicting circRNA-disease associations using meta path-based representation learning on heterogenous network. - Lei Deng 002; Jing Yang; Hui Liu 026 (BIBM, 2020)

Pathway-Guided Deep Neural Network toward Interpretable and Predictive Modeling of Drug Sensitivity. - Lei Deng 002; Yideng Cai; Wenhao Zhang; Wenyi Yang; Bo Gao; Hui Liu 026 (J. Chem. Inf. Model., 2020)

HNet-DNN: Inferring New Drug-Disease Associations with Deep Neural Network Based on Heterogeneous Network Features. - Hui Liu 026; Wenhao Zhang; Yinglong Song; Lei Deng 002; Shuigeng Zhou (J. Chem. Inf. Model., 2020)

DrugCombDB: a comprehensive database of drug combinations toward the discovery of combinatorial therapy. - Hui Liu 026; Wenhao Zhang; Bo Zou; Jinxian Wang; Yuanyuan Deng; Lei Deng 002 (Nucleic Acids Res., 2020)

A multi-task graph convolutional network modeling of drug-drug interactions and synergistic efficacy. - Yuanyuan Deng; Song Yu; Lei Deng 002; Hui Liu 026; Xuejun Liu; Yi Luo (BIBM, 2021)

Contrastive learning-based computational histopathology predict differential expression of cancer driver genes. - Haojie Huang; Gongming Zhou; Xuejun Liu; Lei Deng 002; Chen Wu; Dachuan Zhang; Hui Liu 026 (Briefings Bioinform., 2022)

Attention-wise masked graph contrastive learning for predicting molecular property. - Hui Liu 026; Yibiao Huang; Xuejun Liu; Lei Deng 002 (Briefings Bioinform., 2022)

DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations. - Jinxian Wang; Xuejun Liu; Siyuan Shen; Lei Deng 002; Hui Liu 026 (Briefings Bioinform., 2022)

SynLethDB 2.0: a web-based knowledge graph database on synthetic lethality for novel anticancer drug discovery. - Jie Wang; Min Wu 008; Xuhui Huang; Li Wang; Sophia Zhang; Hui Liu 026; Jie Zheng 002 (Database J. Biol. Databases Curation, 2022)

Graph2MDA: a multi-modal variational graph embedding model for predicting microbe-drug associations. - Lei Deng 002; Yibiao Huang; Xuejun Liu; Hui Liu 026 (Bioinform., 2022)

MSPCD: predicting circRNA-disease associations via integrating multi-source data and hierarchical neural network. - Lei Deng 002; Dayun Liu; Yizhan Li; Runqi Wang; Junyi Liu; Jiaxuan Zhang; Hui Liu 026 (BMC Bioinform., 2022)

Dual-Channel Heterogeneous Graph Neural Network for Predicting microRNA-Mediated Drug Sensitivity. - Lei Deng 002; Ziyu Fan; Xiaojun Xiao; Hui Liu 026; Jiaxuan Zhang (J. Chem. Inf. Model., 2022)

TVPR: Text-to-Video Person Retrieval and a New Benchmark. - Fan Ni; Xu Zhang; Jianhui Wu; Guannan Dong; Aichun Zhu; Hui Liu 026; Yue Zhang (CoRR, 2023)

Interpretable Modeling of Single-cell perturbation Responses to Novel Drugs Using Cycle Consistence Learning. - Wei Huang; Aichun Zhu; Hui Liu 026 (CoRR, 2023)

TVPR: Text-to-Video Person Retrieval and a New Benchmark. - Xu Zhang; Fan Ni; Guannan Dong; Aichun Zhu; Jianhui Wu; Mingcheng Ni; Hui Liu 026 (ACM Multimedia, 2024)

Predicting single-cell cellular responses to perturbations using cycle consistency learning. - Wei Huang; Hui Liu 026 (Bioinform., 2024)

A large language model for predicting T cell receptor-antigen binding specificity. - Xing Fang; Chenpeng Yu; Shiye Tian; Hui Liu 026 (CoRR, 2024)

Contrastive learning-based histopathological features infer molecular subtypes and clinical outcomes of breast cancer from unannotated whole slide images. - Hui Liu 026; Yang Zhang; Judong Luo (Comput. Biol. Medicine, 2024)

Cross-Domain Feature Disentanglement for Interpretable Modeling of Tumor Microenvironment Impact on Drug Response. - Jia Zhai; Hui Liu 026 (IEEE J. Biomed. Health Informatics, 2024)

Learning Cross-Domain Representations for Transferable Drug Perturbations on Single-Cell Transcriptional Responses. - Hui Liu 026; Shikai Jin (AAAI, 2025)

A unified cross-attention model for predicting antigen binding specificity to both HLA and TCR molecules. - Chenpeng Yu; Xing Fang; Shiye Tian; Hui Liu 026 (Nat. Mac. Intell., 2025)

RSSL: A Unified Reliability-Aware Semi-Supervised Learning Framework for Medical Image Classification. - Wenlong Hang; Yecheng Huang; Shuang Liang 015; Yuan Wu; Hui Liu 026; Qiong Wang 001; Ping Liu; Baiying Lei; Harry Qin (IEEE Trans. Emerg. Top. Comput. Intell., 2025)

Predicting Single-Cell Drug Sensitivity Utilizing Adaptive Weighted Features for Multi-Source Domain Adaptation. - Hui Liu 026; Wei Duan; Judong Luo (IEEE J. Biomed. Health Informatics, 2025)