Efficient Frequent Pattern Mining in Relational Databases. - Xuequn Shang 001; Kai-Uwe Sattler; Ingolf Geist (LWA, 2004)

SQL based frequent pattern mining without candidate generation. - Xuequn Shang 001; Kai-Uwe Sattler; Ingolf Geist (SAC, 2004)

SQL Based Frequent Pattern Mining with FP-Growth. - Xuequn Shang 001; Kai-Uwe Sattler; Ingolf Geist (INAP/WLP, 2004)

Frequent Itemset Mining with Parallel RDBMS. - Xuequn Shang 001; Kai-Uwe Sattler (PAKDD, 2005)

Depth-first frequent itemset mining in relational databases. - Xuequn Shang 001; Kai-Uwe Sattler (SAC, 2005)

SQL based frequent pattern mining. - Xuequn Shang 001 (2005)

A Survey of Frequent Pattern Mining for Biological Datasets. - Xuequn Shang 001 (DMIN, 2007)

Processing Sequential Patterns in Relational Databases. - Xuequn Shang 001; Kai-Uwe Sattler (J. Data Semant., 2007)

Sequential Pattern Mining for Protein Function Prediction. - Miao Wang; Xuequn Shang 001; Zhanhuai Li (ADMA, 2008)

Mining High-Correlation Association Rules for Inferring Gene Regulation Networks. - Xuequn Shang 001; Qian Zhao; Zhanhuai Li (DaWaK, 2009)

Mining functional associated patterns from biological network data. - Xuequn Shang 001; Zhanhuai Li; Wei Li (SAC, 2009)

WIBE: Mining Frequent Closed Patterns Without Candidate Maintenance in Microarray Dataset. - Miao Wang; Xuequn Shang 001; Jingni Diao; Zhanhuai Li (DMIN, 2010)

FDCluster: Mining Frequent Closed Discriminative Bicluster without Candidate Maintenance in Multiple Microarray Datasets. - Miao Wang; Xuequn Shang 001; Shaohua Zhang; Zhanhuai Li (ICDM Workshops, 2010)

Efficient Mining Frequent Closed Discriminative Biclusters by Sample-Growth: The FDCluster Approach. - Miao Wang; Xuequn Shang 001; Shaohua Zhang; Zhanhuai Li (Int. J. Knowl. Discov. Bioinform., 2010)

FTCluster: Efficient Mining Fault-Tolerant Biclusters in Microarray Dataset. - Miao Wang; Xuequn Shang 001; Miao Miao; Zhanhuai Li; Wenbin Liu (ICDM Workshops, 2011)

MFCluster: Mining Maximal Fault-Tolerant Constant Row Biclusters in Microarray Dataset. - Miao Wang; Xuequn Shang 001; Miao Miao; Zhanhuai Li; Wenbin Liu (WAIM, 2011)

MFC: Mining Maximal Frequent Dense Subgraphs without Candidate Maintenance in Imbalanced PPI Networks. - Miao Wang; Xuequn Shang 001; Zhanhuai Li (J. Softw., 2011)

Revealing the Causes of Dynamic Change in Protein-Protein Interaction Network. - Yang Guo; Xuequn Shang 001; Jing Li; Zhanhuai Li (BigData Congress, 2013)

Identification of protein complexes and functional modules in integrated PPI networks. - Yang Guo; Xuequn Shang 001; Qingping Zhu; Mingkui Huang; Zhanhuai Li (BIBM, 2014)

A two-step logistic regression algorithm for identifying individual-cancer-related genes. - Bolin Chen; Xuequn Shang 001; Min Li 007; Jianxin Wang 001; Fang-Xiang Wu (BIBM, 2015)

Analyzing factors involved in the HPO-based semantic similarity calculation. - Jiajie Peng; Qianqian Li; Bolin Chen; Jialu Hu; Xuequn Shang 001 (BIBM, 2016)

Measuring phenotype semantic similarity using Human Phenotype Ontology. - Jiajie Peng; Hansheng Xue; Yukai Shao; Xuequn Shang 001; Yadong Wang 001; Jin Chen 004 (BIBM, 2016)

LCM-DS: A novel approach of predicting drug-drug interactions for new drugs via Dempster-Shafer theory of evidence. - Jianyu Shi; Ke Gao; Xue-Qun Shang 001; Siu-Ming Yiu (BIBM, 2016)

Identifying essential proteins based on dynamic protein-protein interaction networks and RNA-Seq datasets. - Xuequn Shang 001; Yu Wang; Bolin Chen (Sci. China Inf. Sci., 2016)

Constrained query of order-preserving submatrix in gene expression data. - Tao Jiang 030; Zhanhuai Li; Xuequn Shang 001; Bolin Chen; Weibang Li; Zhilei Yin (Frontiers Comput. Sci., 2016)

基因表达数据中局部模式的查询 (Local Pattern Query from Gene Expression Data). - Tao Jiang 030; Zhanhuai Li; Xuequn Shang 001; Bolin Chen; Weibang Li (计算机科学, 2016)

Towards the classification of cancer subtypes by using cascade deep forest model in gene expression data. - Yang Guo; Shuhui Liu; Zhanhuai Li; Xuequn Shang 001 (BIBM, 2017)

MiteFinder: A fast approach to identify miniature inverted-repeat transposable elements on a genome-wide scale. - Jialu Hu; Yan Zheng; Xuequn Shang 001 (BIBM, 2017)

Net2Image: A Network Representation Method for Identifying Cancer-Related Genes. - Bolin Chen; Yuqiong Jin; Xuequn Shang 001 (ISBRA, 2017)

Investigations on factors influencing HPO-based semantic similarity calculation. - Jiajie Peng; Qianqian Li; Xuequn Shang 001 (J. Biomed. Semant., 2017)

Identifying term relations cross different gene ontology categories. - Jiajie Peng; Honggang Wang; Junya Lu; Weiwei Hui; Yadong Wang 001; Xuequn Shang 001 (BMC Bioinform., 2017)

A novel method to measure the semantic similarity of HPO terms. - Jiajie Peng; Hansheng Xue; Yukai Shao; Xuequn Shang 001; Yadong Wang 001; Jin Chen 004 (Int. J. Data Min. Bioinform., 2017)

Isometric hashing for image retrieval. - Bo Yang 041; Xuequn Shang 001; Shanmin Pang (Signal Process. Image Commun., 2017)

Identification of lncRNA-disease association using bi-random walks. - Yiqun Gao; Jialu Hu; Xuequn Shang 001 (BIBM, 2018)

TSGOE: A web tool for tissue-specific gene ontology enrichment. - Jiajie Peng; Guilin Lu; Hansheng Xue; Tao Wang 082; Xuequn Shang 001 (BIBM, 2018)

Deep Subspace Similarity Fusion for the Prediction of Cancer Subtypes. - Bo Yang 041; Shuhui Liu; Shanmin Pang; Chenpai Pang; Xuequn Shang 001 (BIBM, 2018)

NetCoffee2: A Novel Global Alignment Algorithm for Multiple PPI Networks Based on Graph Feature Vectors. - Jialu Hu; Junhao He; Yiqun Gao; Yan Zheng; Xuequn Shang 001 (ICIC (2), 2018)

Hierarchical Similarity Network Fusion for Discovering Cancer Subtypes. - Shuhui Liu; Xuequn Shang 001 (ISBRA, 2018)

Low-Rank Graph Regularized Sparse Coding. - Yupei Zhang; Shuhui Liu; Xuequn Shang 001; Ming Xiang (PRICAI (1), 2018)

BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data. - Yang Guo; Shuhui Liu; Zhanhuai Li; Xuequn Shang 001 (BMC Bioinform., 2018)

WebNetCoffee: a web-based application to identify functionally conserved proteins from Multiple PPI networks. - Jialu Hu; Yiqun Gao; Junhao He; Yan Zheng; Xuequn Shang 001 (BMC Bioinform., 2018)

Measuring phenotype-phenotype similarity through the interactome. - Jiajie Peng; Weiwei Hui; Xuequn Shang 001 (BMC Bioinform., 2018)

KF-finder: identification of key factors from host-microbial networks in cervical cancer. - Jialu Hu; Yiqun Gao; Yan Zheng; Xuequn Shang 001 (BMC Syst. Biol., 2018)

Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach. - Jiajie Peng; Xuanshuo Zhang; Weiwei Hui; Junya Lu; Qianqian Li; Shuhui Liu; Xuequn Shang 001 (BMC Syst. Biol., 2018)

Deep Feature Learning of Multi-Network Topology for Node Classification. - Hansheng Xue; Jiajie Peng; Xuequn Shang 001 (CoRR, 2018)

Copy number variation related disease genes. - Chaima Aouiche; Xuequn Shang 001; Bolin Chen (Quant. Biol., 2018)

Towards Gene Function Prediction via Multi-Networks Representation Learning. - Hansheng Xue; Jiajie Peng; Xuequn Shang 001 (AAAI, 2019)

Identifying functional evolution processes according to the pathological stages of colorectal cancer. - Bolin Chen; Manting Yang; Li Gao; Xuequn Shang 001 (BIBM, 2019)

A deconvolution method for predicting cell abundance based on single cell RNA-seq data. - Jiajie Peng; Lu Han; Xuequn Shang 001 (BIBM, 2019)

Deep generative autoencoder for low-dimensional embeding extraction from single-cell RNAseq data. - Shiquan Sun; Yang Liu; Xuequn Shang 001 (BIBM, 2019)

Deep learning enables accurate alignment of single cell RNA-seq data. - Yuanke Zhong; Jing Li; Jie Liu; Yan Zheng; Xuequn Shang 001; Jialu Hu (BIBM, 2019)

Integrating Multi-Network Topology via Deep Semi-supervised Node Embedding. - Hansheng Xue; Jiajie Peng; Jiying Li; Xuequn Shang 001 (CIKM, 2019)

Student Knowledge Diagnosis on Response Data via the Model of Sparse Factor Learning. - Yupei Zhang; Huan Dai; Yue Yun; Xuequn Shang 001 (EDM, 2019)

Identifying Differentially Expressed Genes Based on Differentially Expressed Edges. - Bolin Chen; Li Gao; Xuequn Shang 001 (ICIC (2), 2019)

A Flexible and Comprehensive Platform for Analyzing Gene Expression Data. - Bolin Chen; Chenfei Wang; Li Gao; Xuequn Shang 001 (IDMB, 2019)

Integrating Multiple Datasets to Discover Stage-Specific Cancer Related Genes and Stage-Specific Pathways. - Bolin Chen; Chaima Aouiche; Xuequn Shang 001 (IWBBIO (1), 2019)

A learning-based framework for miRNA-disease association identification using neural networks. - Jiajie Peng; Weiwei Hui; Qianqian Li; Bolin Chen; Jianye Hao; Qinghua Jiang; Xuequn Shang 001; Zhongyu Wei (Bioinform., 2019)

Predicting stage-specific cancer related genes and their dynamic modules by integrating multiple datasets. - Chaima Aouiche; Bolin Chen; Xuequn Shang 001 (BMC Bioinform., 2019)

A novel algorithm based on bi-random walks to identify disease-related lncRNAs. - Jialu Hu; Yiqun Gao; Jing Li; Yan Zheng; Jingru Wang; Xuequn Shang 001 (BMC Bioinform., 2019)

MD-SVM: a novel SVM-based algorithm for the motif discovery of transcription factor binding sites. - Jialu Hu; Jingru Wang; Jianan Lin; Tianwei Liu; Yuanke Zhong; Jie Liu; Yan Zheng; Yiqun Gao; Junhao He; Xuequn Shang 001 (BMC Bioinform., 2019)

TS-GOEA: a web tool for tissue-specific gene set enrichment analysis based on gene ontology. - Jiajie Peng; Guilin Lu; Hansheng Xue; Tao Wang 082; Xuequn Shang 001 (BMC Bioinform., 2019)

Combining gene ontology with deep neural networks to enhance the clustering of single cell RNA-Seq data. - Jiajie Peng; Xiaoyu Wang; Xuequn Shang 001 (BMC Bioinform., 2019)

A fast and efficient count-based matrix factorization method for detecting cell types from single-cell RNAseq data. - Shiquan Sun; Yabo Chen; Yang Liu; Xuequn Shang 001 (BMC Syst. Biol., 2019)

Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO. - Hansheng Xue; Jiajie Peng; Xuequn Shang 001 (BMC Syst. Biol., 2019)

Identification of cancer subtypes by integrating multiple types of transcriptomics data with deep learning in breast cancer. - Yang Guo; Xuequn Shang 001; Zhanhuai Li (Neurocomputing, 2019)

IPMM: Cancer Subtype Clustering Model Based on Multiomics Data and Pathway and Motif Information. - Xinpeng Guo; Yanli Lu; Zhilei Yin; Xuequn Shang 001 (ADMA, 2020)

A Machine Learning Based Method to Identify Differentially Expressed Genes. - Bolin Chen; Li Gao; Xuequn Shang 001 (ICIC (2), 2020)

Identification and Analysis of Genes Involved in Stages of Colon Cancer. - Bolin Chen; Teng Wang; Xuequn Shang 001 (ICIC (2), 2020)

Identifying emerging phenomenon in long temporal phenotyping experiments. - Jiajie Peng; Junya Lu; Donghee Hoh; Ayesha S. Dina; Xuequn Shang 001; David M. Kramer 001; Jin Chen 004 (Bioinform., 2020)

A learning-based method for drug-target interaction prediction based on feature representation learning and deep neural network. - Jiajie Peng; Jingyi Li; Xuequn Shang 001 (BMC Bioinform., 2020)

A flexible network-based imputing-and-fusing approach towards the identification of cell types from single-cell RNA-seq data. - Yang Qi; Yang Guo; Huixin Jiao; Xuequn Shang 001 (BMC Bioinform., 2020)

Twadn: an efficient alignment algorithm based on time warping for pairwise dynamic networks. - Yuanke Zhong; Jing Li; Junhao He; Yiqun Gao; Jie Liu; Jingru Wang; Xuequn Shang 001; Jialu Hu (BMC Bioinform., 2020)

A functional network construction method to interpret the pathological process of colorectal cancer. - Bolin Chen; Manting Yang; Li Gao; Tao Jiang 056; Xuequn Shang 001 (Int. J. Data Min. Bioinform., 2020)

Multidocument Arabic Text Summarization Based on Clustering and Word2Vec to Reduce Redundancy. - Samer Abdulateef; Naseer Ahmed Khan; Bolin Chen; Xuequn Shang 001 (Inf., 2020)

Machine Learning Based Sentiment Text Classification for Evaluating Treatment Quality of Discharge Summary. - Samer Abdulateef; Naseer Ahmed Khan; Bolin Chen; Xuequn Shang 001 (Inf., 2020)

Meta-knowledge dictionary learning on 1-bit response data for student knowledge diagnosis. - Yupei Zhang; Huan Dai; Yue Yun; Shuhui Liu; Andrew S. Lan; Xuequn Shang 001 (Knowl. Based Syst., 2020)

Self-paced Graph Memory Network for Student GPA Prediction and Abnormal Student Detection. - Yue Yun; Huan Dai; Ruoqi Cao; Yupei Zhang; Xuequn Shang 001 (AIED (2), 2021)

Identifying functional evolution processes of cancer according to regression residuals network. - Bolin Chen; Manting Yang; Xuequn Shang 001 (BIBM, 2021)

DCAE: Selecting Discriminative Genes on Single-cell RNA-seq Data for Cell-type Quantification. - Shuhui Liu; Yupei Zhang; Jiajie Peng; Xuequn Shang 001 (BIBM, 2021)

Predicting Hepatoma-Related Genes Based on Representation Learning of PPI network and Gene Ontology Annotations. - Tao Wang 082; Zhiyuan Shao; Yifu Xiao; Xuchao Zhang; Yitian Chen; Binze Shi; Siyu Chen; Yuxian Wang; Jiajie Peng; Xuequn Shang 001 (BIBM, 2021)

VarSKD: A Variational Student Knowledge Diagnosis for Efficiently Representing Student Latent Knowledge Space. - Huan Dai; Yupei Zhang; Yue Yun; Rui An; Xuequn Shang 001 (IEEE BigData, 2021)

Comment Text Grading for Chinese Graduate Academic Dissertation Using Attention Convolutional Neural Networks. - Yupei Zhang; Yaya Zhou; Min Xiao; Xuequn Shang 001 (ICSAI, 2021)

Undergraduate Grade Prediction in Chinese Higher Education Using Convolutional Neural Networks. - Yupei Zhang; Rui An; Jiaqi Cui; Xuequn Shang 001 (LAK, 2021)

An Improved Deep Model for Knowledge Tracing and Question-Difficulty Discovery. - Huan Dai; Yupei Zhang; Yue Yun; Xuequn Shang 001 (PRICAI (2), 2021)

ProTICS reveals prognostic impact of tumor infiltrating immune cells in different molecular subtypes. - Shuhui Liu; Yupei Zhang; Xuequn Shang 001; Zhaolei Zhang (Briefings Bioinform., 2021)

An end-to-end heterogeneous graph representation learning-based framework for drug-target interaction prediction. - Jiajie Peng; Yuxian Wang; Jiaojiao Guan; Jingyi Li; Ruijiang Han; Jianye Hao; Zhongyu Wei; Xuequn Shang 001 (Briefings Bioinform., 2021)

Integrating multi-network topology for gene function prediction using deep neural networks. - Jiajie Peng; Hansheng Xue; Zhongyu Wei; Idil Tuncali; Jianye Hao; Xuequn Shang 001 (Briefings Bioinform., 2021)

A novel method for predicting cell abundance based on single-cell RNA-seq data. - Jiajie Peng; Lu Han; Xuequn Shang 001 (BMC Bioinform., 2021)

SCC: an accurate imputation method for scRNA-seq dropouts based on a mixture model. - Yan Zheng; Yuanke Zhong; Jialu Hu; Xuequn Shang 001 (BMC Bioinform., 2021)

Weakly Supervised Group Mask Network for Object Detection. - Lingyun Song; Jun Liu 002; Mingxuan Sun; Xuequn Shang 001 (Int. J. Comput. Vis., 2021)

Integrating Multi-Omic Data With Deep Subspace Fusion Clustering for Cancer Subtype Prediction. - Bo Yang 041; Yupei Zhang; Shanmin Pang; Xuequn Shang 001; Xueqing Zhao; Minghui Han (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

MMAN: Metapath Based Multi-Level Graph Attention Networks for Heterogeneous Network Embedding (Student Abstract). - Jie Liu; Lingyun Song; Li Gao; Xuequn Shang 001 (AAAI, 2022)

Contrastive Deep Knowledge Tracing. - Huan Dai; Yue Yun; Yupei Zhang; Wenxin Zhang 003; Xuequn Shang 001 (AIED (2), 2022)

Identification of lncRNA-related protein-coding genes using multi-omics data based on deep learning and matrix completion. - Meihong Gao; Xuequn Shang 001 (BIBM, 2022)

A multi-source fusion method to identify biomarkers for breast cancer prognosis based on dual-layer heterogeneous network. - Xingyi Li; Zhelin Zhao; Ju Xiang; Jialu Hu; Xuequn Shang 001 (BIBM, 2022)

CircRNA-Disease Association Prediction based on Heterogeneous Graph Representation. - Xinmeng Liu; Yuhe Zhang; Yewei Shen; Xuequn Shang 001; Yongtian Wang (BIBM, 2022)

Hypergraph-based Gene Ontology Embedding for Disease Gene Prediction. - Tao Wang 082; Hengbo Xu; Ranye Zhang; Yifu Xiao; Jiajie Peng; Xuequn Shang 001 (BIBM, 2022)

Discovering eQTL Regulatory Patterns Through eQTLMotif. - Tao Wang 082; Hui Zhao; Yifu Xiao; Hanzi Yang; Xipeng Yin; Yongtian Wang; Bing Xiao 001; Xuequn Shang 001; Jiajie Peng (BIBM, 2022)

Markov Guided Spatio-Temporal Networks for Brain Image Classification*. - Yupei Zhang; Yunan Xu; Rui An; Yuxin Li; Shuhui Liu; Xuequn Shang 001 (BIBM, 2022)

A Personalized Federated Learning Framework Using Side Information for Heterogeneous Data Classification. - Yupei Zhang; Shuangshuang Wei; Yifei Wang; Yunan Xu; Yuxin Li; Xuequn Shang 001 (IEEE Big Data, 2022)

Personalized Federated Contrastive Learning. - Yupei Zhang; Yunan Xu; Shuangshuang Wei; Yifei Wang; Yuxin Li; Xuequn Shang 001 (IEEE Big Data, 2022)

Topology Imbalance and Relation Inauthenticity Aware Hierarchical Graph Attention Networks for Fake News Detection. - Li Gao; Lingyun Song; Jie Liu; Bolin Chen; Xuequn Shang 001 (COLING, 2022)

Online Deep Knowledge Tracing. - Wenxin Zhang 003; Yupei Zhang; Shuhui Liu; Xuequn Shang 001 (ICDM (Workshops), 2022)

Functional Analysis of Molecular Subtypes with Deep Similarity Learning Model Based on Multi-omics Data. - Shuhui Liu; Yupei Zhang; Xuequn Shang 001 (ICIC (2), 2022)

An Effective Chinese Text Classification Method with Contextualized Weak Supervision for Review Autograding. - Yupei Zhang; Md Shahedul Islam Khan; Yaya Zhou; Min Xiao; Xuequn Shang 001 (ICIC (3), 2022)

Identification of miRNA-lncRNA Underlying Interactions Through Representation for Multiplex Heterogeneous Network. - Ji-Ren Zhou; Zhuhong You; Xuequn Shang 001; Rui Niu; Yue Yun (ICIC (2), 2022)

WeStcoin: Weakly-Supervised Contextualized Text Classification with Imbalance and Noisy Labels. - Yupei Zhang; Yaya Zhou; Shuhui Liu; Wenxin Zhang 003; Min Xiao; Xuequn Shang 001 (ICPR, 2022)

Interpretable Educational Recommendation: An Open Framework based on Bayesian Principal Component Analysis. - Yue Yun; Huan Dai; Yupei Zhang; Shuangshuang Wei; Xuequn Shang 001 (SMC, 2022)

GAE-LGA: integration of multi-omics data with graph autoencoders to identify lncRNA-PCG associations. - Meihong Gao; Shuhui Liu; Yang Qi; Xinpeng Guo; Xuequn Shang 001 (Briefings Bioinform., 2022)

A versatile and scalable single-cell data integration algorithm based on domain-adversarial and variational approximation. - Jialu Hu; Yuanke Zhong; Xuequn Shang 001 (Briefings Bioinform., 2022)

A network-based method for brain disease gene prediction by integrating brain connectome and molecular network. - Wei Wang; Ruijiang Han; Menghan Zhang; Yuxian Wang; Tao Wang 082; Yongtian Wang; Xuequn Shang 001; Jiajie Peng (Briefings Bioinform., 2022)

Enhancing discoveries of molecular QTL studies with small sample size using summary statistic imputation. - Tao Wang 082; Yongzhuang Liu; Quanwei Yin; Jiaquan Geng; Jin Chen 004; Xipeng Yin; Yongtian Wang; Xuequn Shang 001; Chunwei Tian; Yadong Wang 001; Jiajie Peng (Briefings Bioinform., 2022)

Correction to: Enhancing discoveries of molecular QTL studies with small sample size using summary statistic imputation. - Tao Wang 082; Yongzhuang Liu; Quanwei Yin; Jiaquan Geng; Jin Chen 004; Xipeng Yin; Yongtian Wang; Xuequn Shang 001; Chunwei Tian; Yadong Wang 001; Jiajie Peng (Briefings Bioinform., 2022)

A review and performance evaluation of clustering frameworks for single-cell Hi-C data. - Caiwei Zhen; Yuxian Wang; Jiaquan Geng; Lu Han; Jingyi Li; Jinghao Peng; Tao Wang 082; Jianye Hao; Xuequn Shang 001; Zhongyu Wei; Peican Zhu; Jiajie Peng (Briefings Bioinform., 2022)

SEPA: signaling entropy-based algorithm to evaluate personalized pathway activation for survival analysis on pan-cancer data. - Xingyi Li; Min Li 007; Ju Xiang; Zhelin Zhao; Xuequn Shang 001 (Bioinform., 2022)

Flexibility and rigidity index for chromosome packing, flexibility and dynamics analysis. - Jiajie Peng; Jinjin Yang; D. Vijay Anand; Xuequn Shang 001; Kelin Xia (Frontiers Comput. Sci., 2022)

A deep grouping fusion neural network for multimedia content understanding. - Lingyun Song; Mengzhen Yu; Xuequn Shang 001; Yu Lu 003; Jun Liu 002; Ying Zhang; Zhanhuai Li (IET Image Process., 2022)

Graph-regularized federated learning with shareable side information. - Yupei Zhang; Shuangshuang Wei; Shuhui Liu; Yifei Wang; Yunan Xu; Yuxin Li; Xuequn Shang 001 (Knowl. Based Syst., 2022)

Knowledge-Concept Diagnosis from fMRIs by Using a Space-Time Embedding Graph Convolutional Network. - Ye Lei; Yupei Zhang; Yi Lin; Xuequn Shang 001 (WISA, 2023)

Deep Knowledge Tracing with Concept Trees. - Yupei Zhang; Rui An; Wenxin Zhang 003; Shuhui Liu; Xuequn Shang 001 (ADMA (2), 2023)

Learning-Disability Recognition by Using Sparse Spatio-Temporal Graph Neural Networks. - Yuxin Li; Xuequn Shang 001; Yupei Zhang (BIBM, 2023)

A personalized pathway activation inference method based on pathway structure for classification of inflammatory bowel disease. - Xingyi Li; Xuequn Shang 001; Zhelin Zhao; Chenzhuo Yan (BIBM, 2023)

Enhanced RNA Sequence Representation through Sequence Masking and Subsequence Consistency Optimization. - Yewei Shen; Zhiyuan Wang; Zongyu Li; Xinmeng Liu; Xuequn Shang 001; Yongtian Wang (BIBM, 2023)

Deep Learning Integration with Phenotypic Similarities and Heterogeneous Networks for Drug-Target Interaction Prediction. - Yongtian Wang; Li Li; Yewei Shen; Yizhuo Zhang; Yuhe Zhang; Xuequn Shang 001 (BIBM, 2023)

Deep-USIpred: identifying substrates of ubiquitin protein ligases E3 and deubiquitinases with pretrained protein embedding and bayesian neural network. - Jia Wang 008; Gui-Qing Pan; Jian-Qiang Li 001; Xue-Qun Shang 001; Zhu-Hong You; Yu-An Huang (BIBM, 2023)

Course-Graph Discovery from Academic Performance Using Nonnegative LassoNet. - Mengfei Liu; Shuangshuang Wei; Shuhui Liu; Xuequn Shang 001; Yupei Zhang (ICCSE (3), 2023)

Imbalanced Node Classification Beyond Homophilic Assumption. - Jie Liu; Mengting He; Guangtao Wang; Nguyen Quoc Viet Hung; Xuequn Shang 001; Hongzhi Yin (CoRR, 2023)

Concept Prerequisite Relation Prediction by Using Permutation-Equivariant Directed Graph Neural Networks. - Xiran Qu; Xuequn Shang 001; Yupei Zhang (CoRR, 2023)

Meta-HGT: Metapath-aware HyperGraph Transformer for heterogeneous information network embedding. - Jie Liu; Lingyun Song; Guangtao Wang; Xuequn Shang 001 (Neural Networks, 2023)

Answering knowledge-based visual questions via the exploration of Question Purpose. - Lingyun Song; Jianao Li; Jun Liu 002; Yang Yang; Xuequn Shang 001; Mingxuan Sun (Pattern Recognit., 2023)

GLassonet: Identifying Discriminative Gene Sets Among Molecular Subtypes of Breast Cancer. - Shuhui Liu; Yupei Zhang; Xuequn Shang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Attribute-Guided Multiple Instance Hashing Network for Cross-Modal Zero-Shot Hashing. - Lingyun Song; Xuequn Shang 001; Chen Yang; Mingxuan Sun (IEEE Trans. Multim., 2023)

A multi-view latent variable model reveals cellular heterogeneity in complex tissues for paired multimodal single-cell data. - Yuwei Wang; Bin Lian; Haohui Zhang; Yuanke Zhong; Jie He; Fashuai Wu; Knut Reinert; Xuequn Shang 001; Hui Yang; Jialu Hu (Bioinform., 2023)

Predicting and Understanding Student Learning Performance Using Multi-Source Sparse Attention Convolutional Neural Networks. - Yupei Zhang; Rui An; Shuhui Liu; Jiaqi Cui; Xuequn Shang 001 (IEEE Trans. Big Data, 2023)

Collaborative deep learning improves disease-related circRNA prediction based on multi-source functional information. - Yongtian Wang; Xinmeng Liu; Yewei Shen; Xuerui Song; Tao Wang 082; Xuequn Shang 001; Jiajie Peng (Briefings Bioinform., 2023)

SVsearcher: A more accurate structural variation detection method in long read data. - Yan Zheng; Xuequn Shang 001; Wing-Kin Sung (Comput. Biol. Medicine, 2023)

Doubly contrastive representation learning for federated image recognition. - Yupei Zhang; Yunan Xu; Shuangshuang Wei; Yifei Wang; Yuxin Li; Xuequn Shang 001 (Pattern Recognit., 2023)

scMultiGAN: cell-specific imputation for single-cell transcriptomes with multiple deep generative adversarial networks. - Tao Wang 082; Hui Zhao; Yungang Xu; Yongtian Wang; Xuequn Shang 001; Jiajie Peng; Bing Xiao 001 (Briefings Bioinform., 2023)

A deep cross-modal neural cognitive diagnosis framework for modeling student performance. - Lingyun Song; Mengting He; Xuequn Shang 001; Chen Yang; Jun Liu 002; Mengzhen Yu; Yu Lu 003 (Expert Syst. Appl., 2023)

SVcnn: an accurate deep learning-based method for detecting structural variation based on long-read data. - Yan Zheng; Xuequn Shang 001 (BMC Bioinform., 2023)

Temporal Graph Cube. - Guoren Wang; Yue Zeng 004; Rong-Hua Li; Hongchao Qin; Xuanhua Shi; Yubin Xia; Xuequn Shang 001; Liang Hong (IEEE Trans. Knowl. Data Eng., 2023)

TRoute: Dynamic Time-Dependent Route Recommendation on Road Networks. - Xiaolin Han 002; Xiurui Hu; Chenhao Ma 001; Xuequn Shang 001 (WISA, 2024)

DMGNN: cancer driver gene identification based on mix-moment graph neural network. - Bolin Chen; Ziyuan Li; Haodong Li; Junming Li; Ruiming Kang; Xuequn Shang 001; Jun Bian (BIBM, 2024)

The identification of stage-related driving factors in breast carcinoma based on network smoothing and gravity model. - Bolin Chen; Jinlei Zhang; Yourui Han; Jun Bian; Xuequn Shang 001 (BIBM, 2024)

SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection. - Zhihao Ding; Jieming Shi 001; Shiqi Shen; Xuequn Shang 001; Jiannong Cao 001; Zhipeng Wang; Zhi Gong (CIKM, 2024)

A Robust Dual-debiasing VQA Model based on Counterfactual Causal Effect. - Lingyun Song; Chengkun Yang; Xuanyu Li; Xuequn Shang 001 (EMNLP (Findings), 2024)

BOURNE: Bootstrapped Self-Supervised Learning Framework for Unified Graph Anomaly Detection. - Jie Liu; Mengting He; Xuequn Shang 001; Jieming Shi 001; Bin Cui 001; Hongzhi Yin (ICDE, 2024)

The mathematical exploration for the mechanism of lung adenocarcinoma formation and progression. - Yourui Han; Bolin Chen; Zhongwen Bi; Jun Bian; Ruiming Kang; Xuequn Shang 001 (Briefings Bioinform., 2024)

Cancerous time estimation for interpreting the evolution of lung adenocarcinoma. - Yourui Han; Bolin Chen; Jun Bian; Ruiming Kang; Xuequn Shang 001 (Briefings Bioinform., 2024)

Towards simplified graph neural networks for identifying cancer driver genes in heterophilic networks. - Xingyi Li; Jialuo Xu; Junming Li; Jia Gu; Xuequn Shang 001 (Briefings Bioinform., 2024)

Attention-aware differential learning for predicting peptide-MHC class I binding and T cell receptor recognition. - Rui Niu; Jingwei Wang; Yanli Li; Jiren Zhou; Yang Guo; Xuequn Shang 001 (Briefings Bioinform., 2024)

Accurately deciphering spatial domains for spatially resolved transcriptomics with stCluster. - Tao Wang 082; Han Shu; Jialu Hu; Yongtian Wang; Jin Chen 004; Jiajie Peng; Xuequn Shang 001 (Briefings Bioinform., 2024)

Predicting drug-target binding affinity with cross-scale graph contrastive learning. - Jingru Wang; Yihang Xiao; Xuequn Shang 001; Jiajie Peng (Briefings Bioinform., 2024)

Multiplex Networks and Pan-Cancer Multiomics-Based Driver Gene Identification Using Graph Neural Networks. - Xingyi Li; Junming Li; Jun Hao; Xingyu Liao; Min Li 007; Xuequn Shang 001 (Big Data Min. Anal., 2024)

QIGTD: identifying critical genes in the evolution of lung adenocarcinoma with tensor decomposition. - Bolin Chen; Jinlei Zhang; Ci Shao; Jun Bian; Ruiming Kang; Xuequn Shang 001 (BioData Min., 2024)

postGWAS: A web server for deciphering the causality post the genome-wide association studies. - Tao Wang 082; Zhihao Yan; Yiming Zhang; Zhuofei Lou; Xiaozhu Zheng; Duoduo Mai; Yongtian Wang; Xuequn Shang 001; Bing Xiao 001; Jiajie Peng; Jin Chen 004 (Comput. Biol. Medicine, 2024)

Spatial-temporal Memories Enhanced Graph Autoencoder for Anomaly Detection in Dynamic Graphs. - Jie Liu; Xuequn Shang 001; Xiaolin Han 002; Wentao Zhang 001; Hongzhi Yin (CoRR, 2024)

Cooperative SQL Generation for Segmented Databases By Using Multi-functional LLM Agents. - Zhiguang Wu; Fengbin Zhu; Xuequn Shang 001; Yupei Zhang; Pan Zhou (CoRR, 2024)

Adaptive meta-knowledge dictionary learning for incremental knowledge tracing. - Huan Dai; Yupei Zhang; Yue Yun; Rui An; Wenxin Zhang 003; Xuequn Shang 001 (Eng. Appl. Artif. Intell., 2024)

Self-paced contrastive learning for knowledge tracing. - Huan Dai; Yue Yun; Yupei Zhang; Rui An; Wenxin Zhang 003; Xuequn Shang 001 (Neurocomputing, 2024)

Weakly supervised text classification framework for noisy-labeled imbalanced samples. - Wenxin Zhang 003; Yaya Zhou; Shuhui Liu; Yupei Zhang; Xuequn Shang 001 (Neurocomputing, 2024)

FDM: Effective and efficient incident detection on sparse trajectory data. - Xiaolin Han 002; Tobias Grubenmann; Chenhao Ma 001; Xiaodong Li 009; Wenya Sun; Sze Chun Wong; Xuequn Shang 001; Reynold Cheng (Inf. Syst., 2024)

Doubly constrained offline reinforcement learning for learning path recommendation. - Yue Yun; Huan Dai; Rui An; Yupei Zhang; Xuequn Shang 001 (Knowl. Based Syst., 2024)

A hierarchical GNN across semantic and topological domains for predicting circRNA-microRNA interactions. - Ji-Ren Zhou; Boya Ji; Rui Niu; Xuequn Shang 001; Zhuhong You (Knowl. Based Syst., 2024)

A Multi-Group Multi-Stream attribute Attention network for fine-grained zero-shot learning. - Lingyun Song; Xuequn Shang 001; Ruizhi Zhou; Jun Liu 002; Jie Ma 001; Zhanhuai Li; Mingxuan Sun (Neural Networks, 2024)

FMSA-SC: A Fine-Grained Multimodal Sentiment Analysis Dataset Based on Stock Comment Videos. - Lingyun Song; Siyu Chen; Ziyang Meng 002; Mingxuan Sun; Xuequn Shang 001 (IEEE Trans. Multim., 2024)

Enhancing Enterprise Credit Risk Assessment with Cascaded Multi-level Graph Representation Learning. - Lingyun Song; Haodong Li; Yacong Tan; Zhanhuai Li; Xuequn Shang 001 (Neural Networks, 2024)

Scbean: a python library for single-cell multi-omics data analysis. - Haohui Zhang; Yuwei Wang; Bin Lian; Yiran Wang; Xingyi Li; Tao Wang 082; Xuequn Shang 001; Hui Yang; Ahmad Aziz; Jialu Hu (Bioinform., 2024)

FindCSV: a long-read based method for detecting complex structural variations. - Yan Zheng; Xuequn Shang 001 (BMC Bioinform., 2024)

Federated learning-outcome prediction with multi-layer privacy protection. - Yupei Zhang; Yuxin Li; Yifei Wang; Shuangshuang Wei; Yunan Xu; Xuequn Shang 001 (Frontiers Comput. Sci., 2024)

Learning Path Planning via Prior-Guided Reinforcement Learning. - Mengfei Liu; Xian-Sheng Hua 001; Xuequn Shang 001; Yupei Zhang (AIED (6), 2025)

ReadGraph: Relational Evolution Enhanced Anomaly Detection in Dynamic Heterogeneous Graph. - Xiaolin Han 002; Xiurui Hu; Chenhao Ma 001; Xuequn Shang 001 (WWW (Companion Volume), 2025)

Logic-Aware Knowledge Graph Reasoning for Structural Sparsity under Large Language Model Supervision. - Yudai Pan; Jiajie Hong; Tianzhe Zhao; Lingyun Song; Jun Liu 002; Xuequn Shang 001 (WWW, 2025)

Inference of gene coexpression networks from single-cell transcriptome data based on variance decomposition analysis. - Bin Lian; Haohui Zhang; Tao Wang 082; Yongtian Wang; Xuequn Shang 001; N. Ahmad Aziz; Jialu Hu (Briefings Bioinform., 2025)

Deep graph convolutional network-based multi-omics integration for cancer driver gene identification. - Yingzhuo Wu; Jialuo Xu; Junming Li; Jia Gu; Xuequn Shang 001; Xingyi Li (Briefings Bioinform., 2025)

cfMethylPre: deep transfer learning enhances cancer detection based on circulating cell-free DNA methylation profiling. - Xuchao Zhang; Jing Chen; Yongtian Wang; Xiaofeng Wang; Jialu Hu; Jiajie Peng; Xuequn Shang 001; Yanpu Wang; Tao Wang 082 (Briefings Bioinform., 2025)

MAEST: accurately spatial domain detection in spatial transcriptomics with graph masked autoencoder. - Pengfei Zhu; Han Shu; Yongtian Wang; Xiaofeng Wang; Yuan Zhao; Jialu Hu; Jiajie Peng; Xuequn Shang 001; Zhen Tian; Jing Chen; Tao Wang 082 (Briefings Bioinform., 2025)

Cross-modal multi-relational graph reasoning: A novel model for multimodal textbook comprehension. - Lingyun Song; Wenqing Du; Xiaolin Han 002; Xinbiao Gan; Xiaoqi Wang; Xuequn Shang 001 (Inf. Fusion, 2025)

Harnessing the potential of multimodal EHR data: A comprehensive survey of clinical predictive modeling for intelligent healthcare. - Jialun Wu; Kai He 001; Rui Mao 010; Xuequn Shang 001; Erik Cambria (Inf. Fusion, 2025)

Federated Deep Subspace Clustering. - Yupei Zhang; Ruojia Feng; Yifei Wang; Xuequn Shang 001 (CoRR, 2025)

scGSDR: Harnessing Gene Semantics for Single-Cell Pharmacological Profiling. - Yu-An Huang; Xiyue Cao; Zhu-Hong You; Yue-Chao Li; Xuequn Shang 001; Zhi-An Huang (CoRR, 2025)

Federated Discriminative Representation Learning for Image Classification. - Yupei Zhang; Yifei Wang; Yuxin Li; Yunan Xu; Shuangshuang Wei; Shuhui Liu; Xuequn Shang 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

PathActMarker: an R package for inferring pathway activity of complex diseases. - Xingyi Li; Jun Hao; Zhelin Zhao; Junming Li; Xingyu Liao; Min Li 007; Xuequn Shang 001 (Frontiers Comput. Sci., 2025)

Multi-instance discriminative contrastive learning for brain image representation. - Yupei Zhang; Shuhui Liu; Xiran Qu; Xuequn Shang 001 (Neural Comput. Appl., 2025)

Hypergraph-Enhanced Multi-Granularity Stochastic Weight Completion in Sparse Road Networks. - Xiaolin Han 002; Yikun Zhang; Chenhao Ma 001; Xuequn Shang 001; Reynold Cheng; Tobias Grubenmann; Xiaodong Li 009 (ACM Trans. Knowl. Discov. Data, 2025)

Damba-ST: Domain-Adaptive Mamba for Efficient Urban Spatio-Temporal Prediction. - Rui An; Yifeng Zhang 007; Ziran Liang; Wenqi Fan; Yuxuan Liang; Xuequn Shang 001; Qing Li 001 (CoRR, 2025)

Multiscale Weisfeiler-Leman Directed Graph Neural Networks for Prerequisite-Link Prediction. - Yupei Zhang; Xiran Qu; Shuhui Liu; Yan Pang; Xuequn Shang 001 (IEEE Trans. Knowl. Data Eng., 2025)

Local-Global Structure-Aware Geometric Equivariant Graph Representation Learning for Predicting Protein-Ligand Binding Affinity. - Shihong Chen; Haicheng Yi; Zhuhong You; Xuequn Shang 001; Yu-An Huang; Lei Wang 121; Zhen Wang 020 (IEEE Trans. Neural Networks Learn. Syst., 2025)