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Xue-Qun Shang
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2020 – today
- 2024
[j75]Tao Wang, Han Shu, Jialu Hu
, Yongtian Wang, Jin Chen, Jiajie Peng, Xuequn Shang:
Accurately deciphering spatial domains for spatially resolved transcriptomics with stCluster. Briefings Bioinform. 25(4) (2024)- [j74]Haohui Zhang, Yuwei Wang, Bin Lian, Yiran Wang, Xingyi Li, Tao Wang, Xuequn Shang, Hui Yang, Ahmad Aziz, Jialu Hu:
Scbean: a python library for single-cell multi-omics data analysis. Bioinform. 40(2) (2024) - [j73]Yan Zheng, Xuequn Shang:
FindCSV: a long-read based method for detecting complex structural variations. BMC Bioinform. 25(1): 315 (2024) - [j72]Tao Wang, Zhihao Yan, Yiming Zhang, Zhuofei Lou, Xiaozhu Zheng, Duoduo Mai, Yongtian Wang, Xuequn Shang, Bing Xiao, Jiajie Peng, Jin Chen:
postGWAS: A web server for deciphering the causality post the genome-wide association studies. Comput. Biol. Medicine 171: 108108 (2024) - [j71]Huan Dai, Yupei Zhang, Yue Yun, Rui An, Wenxin Zhang, Xuequn Shang:
Adaptive meta-knowledge dictionary learning for incremental knowledge tracing. Eng. Appl. Artif. Intell. 132: 107969 (2024) - [j70]Yupei Zhang, Yuxin Li, Yifei Wang, Shuangshuang Wei, Yunan Xu, Xuequn Shang:
Federated learning-outcome prediction with multi-layer privacy protection. Frontiers Comput. Sci. 18(6): 186604 (2024) - [j69]Huan Dai, Yue Yun, Yupei Zhang, Rui An, Wenxin Zhang, Xuequn Shang:
Self-paced contrastive learning for knowledge tracing. Neurocomputing 609: 128366 (2024) - [j68]Wenxin Zhang, Yaya Zhou, Shuhui Liu, Yupei Zhang, Xuequn Shang:
Weakly supervised text classification framework for noisy-labeled imbalanced samples. Neurocomputing 610: 128617 (2024) - [j67]Xiaolin Han, Tobias Grubenmann, Chenhao Ma, Xiaodong Li, Wenya Sun, Sze Chun Wong, Xuequn Shang, Reynold Cheng:
FDM: Effective and efficient incident detection on sparse trajectory data. Inf. Syst. 125: 102418 (2024) - [j66]Yue Yun, Huan Dai, Rui An, Yupei Zhang, Xuequn Shang:
Doubly constrained offline reinforcement learning for learning path recommendation. Knowl. Based Syst. 284: 111242 (2024) - [j65]Ji-Ren Zhou, Boya Ji, Rui Niu, Xuequn Shang, Zhuhong You:
A hierarchical GNN across semantic and topological domains for predicting circRNA-microRNA interactions. Knowl. Based Syst. 304: 112549 (2024) - [j64]Lingyun Song, Haodong Li, Yacong Tan, Zhanhuai Li, Xuequn Shang:
Enhancing Enterprise Credit Risk Assessment with Cascaded Multi-level Graph Representation Learning. Neural Networks 169: 475-484 (2024) - [j63]Lingyun Song, Xuequn Shang, Ruizhi Zhou, Jun Liu, Jie Ma, Zhanhuai Li, Mingxuan Sun:
A Multi-Group Multi-Stream attribute Attention network for fine-grained zero-shot learning. Neural Networks 179: 106558 (2024) - [j62]Lingyun Song, Siyu Chen, Ziyang Meng, Mingxuan Sun, Xuequn Shang:
FMSA-SC: A Fine-Grained Multimodal Sentiment Analysis Dataset Based on Stock Comment Videos. IEEE Trans. Multim. 26: 7294-7306 (2024) - [c78]Xiaolin Han, Xiurui Hu, Chenhao Ma, Xuequn Shang:
TRoute: Dynamic Time-Dependent Route Recommendation on Road Networks. WISA 2024: 573-585 - [c77]Jie Liu, Mengting He, Xuequn Shang, Jieming Shi, Bin Cui, Hongzhi Yin:
BOURNE: Bootstrapped Self-Supervised Learning Framework for Unified Graph Anomaly Detection. ICDE 2024: 2820-2833 - [e1]Cheqing Jin, Shiyu Yang, Xuequn Shang, Haofen Wang, Yong Zhang:
Web Information Systems and Applications - 21st International Conference, WISA 2024, Yinchuan, China, August 2-4, 2024, Proceedings. Lecture Notes in Computer Science 14883, Springer 2024, ISBN 978-981-97-7706-8 [contents] - [i6]Jie Liu, Xuequn Shang, Xiaolin Han, Wentao Zhang, Hongzhi Yin:
Spatial-temporal Memories Enhanced Graph Autoencoder for Anomaly Detection in Dynamic Graphs. CoRR abs/2403.09039 (2024) - 2023
- [j61]Yongtian Wang, Xinmeng Liu, Yewei Shen, Xuerui Song, Tao Wang, Xuequn Shang, Jiajie Peng:
Collaborative deep learning improves disease-related circRNA prediction based on multi-source functional information. Briefings Bioinform. 24(2) (2023) - [j60]Yuwei Wang, Bin Lian, Haohui Zhang, Yuanke Zhong, Jie He, Fashuai Wu, Knut Reinert, Xuequn Shang, Hui Yang, Jialu Hu:
A multi-view latent variable model reveals cellular heterogeneity in complex tissues for paired multimodal single-cell data. Bioinform. 39(1) (2023) - [j59]Yan Zheng, Xuequn Shang:
SVcnn: an accurate deep learning-based method for detecting structural variation based on long-read data. BMC Bioinform. 24(1): 213 (2023) - [j58]Yan Zheng, Xuequn Shang, Wing-Kin Sung:
SVsearcher: A more accurate structural variation detection method in long read data. Comput. Biol. Medicine 158: 106843 (2023) - [j57]Lingyun Song, Mengting He, Xuequn Shang, Chen Yang, Jun Liu, Mengzhen Yu, Yu Lu:
A deep cross-modal neural cognitive diagnosis framework for modeling student performance. Expert Syst. Appl. 230: 120675 (2023) - [j56]Jie Liu, Lingyun Song, Guangtao Wang, Xuequn Shang:
Meta-HGT: Metapath-aware HyperGraph Transformer for heterogeneous information network embedding. Neural Networks 157: 65-76 (2023) - [j55]Lingyun Song, Jianao Li, Jun Liu, Yang Yang, Xuequn Shang, Mingxuan Sun:
Answering knowledge-based visual questions via the exploration of Question Purpose. Pattern Recognit. 133: 109015 (2023) - [j54]Yupei Zhang, Yunan Xu, Shuangshuang Wei, Yifei Wang, Yuxin Li, Xuequn Shang:
Doubly contrastive representation learning for federated image recognition. Pattern Recognit. 139: 109507 (2023) - [j53]Yupei Zhang, Rui An, Shuhui Liu, Jiaqi Cui, Xuequn Shang:
Predicting and Understanding Student Learning Performance Using Multi-Source Sparse Attention Convolutional Neural Networks. IEEE Trans. Big Data 9(1): 118-132 (2023) - [j52]Shuhui Liu, Yupei Zhang, Xuequn Shang:
GLassonet: Identifying Discriminative Gene Sets Among Molecular Subtypes of Breast Cancer. IEEE ACM Trans. Comput. Biol. Bioinform. 20(3): 1905-1916 (2023) - [j51]Guoren Wang, Yue Zeng, Rong-Hua Li, Hongchao Qin, Xuanhua Shi, Yubin Xia, Xuequn Shang, Liang Hong:
Temporal Graph Cube. IEEE Trans. Knowl. Data Eng. 35(12): 13015-13030 (2023) - [j50]Lingyun Song, Xuequn Shang, Chen Yang, Mingxuan Sun:
Attribute-Guided Multiple Instance Hashing Network for Cross-Modal Zero-Shot Hashing. IEEE Trans. Multim. 25: 5305-5318 (2023) - [c76]Ye Lei, Yupei Zhang, Yi Lin, Xuequn Shang:
Knowledge-Concept Diagnosis from fMRIs by Using a Space-Time Embedding Graph Convolutional Network. WISA 2023: 100-111 - [c75]Yupei Zhang, Rui An, Wenxin Zhang, Shuhui Liu, Xuequn Shang:
Deep Knowledge Tracing with Concept Trees. ADMA (2) 2023: 377-390 - [c74]Xingyi Li, Xuequn Shang, Zhelin Zhao, Chenzhuo Yan:
A personalized pathway activation inference method based on pathway structure for classification of inflammatory bowel disease. BIBM 2023: 171-176 - [c73]Jia Wang, Gui-Qing Pan, Jian-Qiang Li, Xue-Qun Shang, Zhu-Hong You, Yu-An Huang:
Deep-USIpred: identifying substrates of ubiquitin protein ligases E3 and deubiquitinases with pretrained protein embedding and bayesian neural network. BIBM 2023: 2277-2280 - [c72]Yewei Shen, Zhiyuan Wang, Zongyu Li, Xinmeng Liu, Xuequn Shang, Yongtian Wang:
Enhanced RNA Sequence Representation through Sequence Masking and Subsequence Consistency Optimization. BIBM 2023: 2938-2944 - [c71]Yongtian Wang, Li Li, Yewei Shen, Yizhuo Zhang, Yuhe Zhang, Xuequn Shang:
Deep Learning Integration with Phenotypic Similarities and Heterogeneous Networks for Drug-Target Interaction Prediction. BIBM 2023: 2945-2951 - [c70]Yuxin Li, Xuequn Shang, Yupei Zhang:
Learning-Disability Recognition by Using Sparse Spatio-Temporal Graph Neural Networks. BIBM 2023: 3521-3528 - [c69]Mengfei Liu, Shuangshuang Wei, Shuhui Liu, Xuequn Shang, Yupei Zhang:
Course-Graph Discovery from Academic Performance Using Nonnegative LassoNet. ICCSE (3) 2023: 364-370 - [i5]Jie Liu, Mengting He, Guangtao Wang, Nguyen Quoc Viet Hung, Xuequn Shang, Hongzhi Yin:
Imbalanced Node Classification Beyond Homophilic Assumption. CoRR abs/2304.14635 (2023) - [i4]Jie Liu, Mengting He, Xuequn Shang, Jieming Shi, Bin Cui, Hongzhi Yin:
BOURNE: Bootstrapped Self-supervised Learning Framework for Unified Graph Anomaly Detection. CoRR abs/2307.15244 (2023) - [i3]Xiran Qu, Xuequn Shang, Yupei Zhang:
Concept Prerequisite Relation Prediction by Using Permutation-Equivariant Directed Graph Neural Networks. CoRR abs/2312.09802 (2023) - [i2]Yupei Zhang, Yuxin Li, Yifei Wang, Shuangshuang Wei, Yunan Xu, Xuequn Shang:
Federated learning-outcome prediction with multi-layer privacy protection. CoRR abs/2312.15608 (2023) - 2022
- [j49]Jialu Hu, Yuanke Zhong, Xuequn Shang:
A versatile and scalable single-cell data integration algorithm based on domain-adversarial and variational approximation. Briefings Bioinform. 23(1) (2022) - [j48]Wei Wang, Ruijiang Han, Menghan Zhang, Yuxian Wang, Tao Wang, Yongtian Wang, Xuequn Shang, Jiajie Peng:
A network-based method for brain disease gene prediction by integrating brain connectome and molecular network. Briefings Bioinform. 23(1) (2022) - [j47]Tao Wang, Yongzhuang Liu, Quanwei Yin, Jiaquan Geng, Jin Chen, Xipeng Yin, Yongtian Wang, Xuequn Shang, Chunwei Tian, Yadong Wang, Jiajie Peng:
Enhancing discoveries of molecular QTL studies with small sample size using summary statistic imputation. Briefings Bioinform. 23(1) (2022) - [j46]Tao Wang, Yongzhuang Liu, Quanwei Yin, Jiaquan Geng, Jin Chen, Xipeng Yin, Yongtian Wang, Xuequn Shang, Chunwei Tian, Yadong Wang, Jiajie Peng:
Correction to: Enhancing discoveries of molecular QTL studies with small sample size using summary statistic imputation. Briefings Bioinform. 23(3) (2022) - [j45]Meihong Gao, Shuhui Liu, Yang Qi, Xinpeng Guo, Xuequn Shang:
GAE-LGA: integration of multi-omics data with graph autoencoders to identify lncRNA-PCG associations. Briefings Bioinform. 23(6) (2022) - [j44]Caiwei Zhen, Yuxian Wang, Jiaquan Geng, Lu Han, Jingyi Li, Jinghao Peng, Tao Wang, Jianye Hao, Xuequn Shang, Zhongyu Wei, Peican Zhu, Jiajie Peng:
A review and performance evaluation of clustering frameworks for single-cell Hi-C data. Briefings Bioinform. 23(6) (2022) - [j43]Jiajie Peng, Jinjin Yang, D. Vijay Anand, Xuequn Shang, Kelin Xia:
Flexibility and rigidity index for chromosome packing, flexibility and dynamics analysis. Frontiers Comput. Sci. 16(4): 164902 (2022) - [j42]Lingyun Song, Mengzhen Yu, Xuequn Shang, Yu Lu, Jun Liu, Ying Zhang, Zhanhuai Li:
A deep grouping fusion neural network for multimedia content understanding. IET Image Process. 16(9): 2398-2411 (2022) - [j41]Yupei Zhang, Shuangshuang Wei, Shuhui Liu, Yifei Wang, Yunan Xu, Yuxin Li, Xuequn Shang:
Graph-regularized federated learning with shareable side information. Knowl. Based Syst. 257: 109960 (2022) - [c68]Jie Liu, Lingyun Song, Li Gao, Xuequn Shang:
MMAN: Metapath Based Multi-Level Graph Attention Networks for Heterogeneous Network Embedding (Student Abstract). AAAI 2022: 13005-13006 - [c67]Huan Dai, Yue Yun, Yupei Zhang, Wenxin Zhang, Xuequn Shang:
Contrastive Deep Knowledge Tracing. AIED (2) 2022: 289-292 - [c66]Tao Wang, Hui Zhao, Yifu Xiao, Hanzi Yang, Xipeng Yin, Yongtian Wang, Bing Xiao, Xuequn Shang, Jiajie Peng:
Discovering eQTL Regulatory Patterns Through eQTLMotif. BIBM 2022: 130-135 - [c65]Xingyi Li, Zhelin Zhao, Ju Xiang, Jialu Hu, Xuequn Shang:
A multi-source fusion method to identify biomarkers for breast cancer prognosis based on dual-layer heterogeneous network. BIBM 2022: 471-476 - [c64]Yupei Zhang, Yunan Xu, Rui An, Yuxin Li, Shuhui Liu, Xuequn Shang:
Markov Guided Spatio-Temporal Networks for Brain Image Classification*. BIBM 2022: 2035-2041 - [c63]Xinmeng Liu, Yuhe Zhang, Yewei Shen, Xuequn Shang, Yongtian Wang:
CircRNA-Disease Association Prediction based on Heterogeneous Graph Representation. BIBM 2022: 2411-2417 - [c62]Tao Wang, Hengbo Xu, Ranye Zhang, Yifu Xiao, Jiajie Peng, Xuequn Shang:
Hypergraph-based Gene Ontology Embedding for Disease Gene Prediction. BIBM 2022: 2424-2430 - [c61]Meihong Gao, Xuequn Shang:
Identification of lncRNA-related protein-coding genes using multi-omics data based on deep learning and matrix completion. BIBM 2022: 3307-3314 - [c60]Yupei Zhang, Shuangshuang Wei, Yifei Wang, Yunan Xu, Yuxin Li, Xuequn Shang:
A Personalized Federated Learning Framework Using Side Information for Heterogeneous Data Classification. IEEE Big Data 2022: 3455-3461 - [c59]Yupei Zhang, Yunan Xu, Shuangshuang Wei, Yifei Wang, Yuxin Li, Xuequn Shang:
Personalized Federated Contrastive Learning. IEEE Big Data 2022: 4218-4225 - [c58]Li Gao, Lingyun Song, Jie Liu, Bolin Chen, Xuequn Shang:
Topology Imbalance and Relation Inauthenticity Aware Hierarchical Graph Attention Networks for Fake News Detection. COLING 2022: 4687-4696 - [c57]Wenxin Zhang, Yupei Zhang, Shuhui Liu, Xuequn Shang:
Online Deep Knowledge Tracing. ICDM (Workshops) 2022: 292-297 - [c56]Shuhui Liu, Yupei Zhang, Xuequn Shang:
Functional Analysis of Molecular Subtypes with Deep Similarity Learning Model Based on Multi-omics Data. ICIC (2) 2022: 126-137 - [c55]Yupei Zhang, Md Shahedul Islam Khan, Yaya Zhou, Min Xiao, Xuequn Shang:
An Effective Chinese Text Classification Method with Contextualized Weak Supervision for Review Autograding. ICIC (3) 2022: 170-182 - [c54]Ji-Ren Zhou, Zhuhong You, Xuequn Shang, Rui Niu, Yue Yun:
Identification of miRNA-lncRNA Underlying Interactions Through Representation for Multiplex Heterogeneous Network. ICIC (2) 2022: 270-277 - [c53]Yupei Zhang, Yaya Zhou, Shuhui Liu, Wenxin Zhang, Min Xiao, Xuequn Shang:
WeStcoin: Weakly-Supervised Contextualized Text Classification with Imbalance and Noisy Labels. ICPR 2022: 2451-2457 - [c52]Yue Yun, Huan Dai, Yupei Zhang, Shuangshuang Wei, Xuequn Shang:
Interpretable Educational Recommendation: An Open Framework based on Bayesian Principal Component Analysis. SMC 2022: 3409-3414 - 2021
- [j40]Jiajie Peng, Hansheng Xue, Zhongyu Wei, Idil Tuncali, Jianye Hao, Xuequn Shang:
Integrating multi-network topology for gene function prediction using deep neural networks. Briefings Bioinform. 22(2): 2096-2105 (2021) - [j39]Jiajie Peng, Yuxian Wang, Jiaojiao Guan, Jingyi Li, Ruijiang Han, Jianye Hao, Zhongyu Wei, Xuequn Shang:
An end-to-end heterogeneous graph representation learning-based framework for drug-target interaction prediction. Briefings Bioinform. 22(5) (2021) - [j38]Shuhui Liu, Yupei Zhang, Xuequn Shang, Zhaolei Zhang:
ProTICS reveals prognostic impact of tumor infiltrating immune cells in different molecular subtypes. Briefings Bioinform. 22(6) (2021) - [j37]Yan Zheng, Yuanke Zhong, Jialu Hu, Xuequn Shang:
SCC: an accurate imputation method for scRNA-seq dropouts based on a mixture model. BMC Bioinform. 22(1): 5 (2021) - [j36]Jiajie Peng, Lu Han, Xuequn Shang:
A novel method for predicting cell abundance based on single-cell RNA-seq data. BMC Bioinform. 22-S(9): 281 (2021) - [j35]Lingyun Song, Jun Liu, Mingxuan Sun, Xuequn Shang:
Weakly Supervised Group Mask Network for Object Detection. Int. J. Comput. Vis. 129(3): 681-702 (2021) - [j34]Bo Yang, Yupei Zhang, Shanmin Pang, Xuequn Shang, Xueqing Zhao, Minghui Han:
Integrating Multi-Omic Data With Deep Subspace Fusion Clustering for Cancer Subtype Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 18(1): 216-226 (2021) - [c51]Yue Yun, Huan Dai, Ruoqi Cao, Yupei Zhang, Xuequn Shang:
Self-paced Graph Memory Network for Student GPA Prediction and Abnormal Student Detection. AIED (2) 2021: 417-421 - [c50]Shuhui Liu, Yupei Zhang, Jiajie Peng, Xuequn Shang:
DCAE: Selecting Discriminative Genes on Single-cell RNA-seq Data for Cell-type Quantification. BIBM 2021: 1865-1872 - [c49]Tao Wang, Zhiyuan Shao, Yifu Xiao, Xuchao Zhang, Yitian Chen, Binze Shi, Siyu Chen, Yuxian Wang, Jiajie Peng, Xuequn Shang:
Predicting Hepatoma-Related Genes Based on Representation Learning of PPI network and Gene Ontology Annotations. BIBM 2021: 1892-1898 - [c48]Bolin Chen, Manting Yang, Xuequn Shang:
Identifying functional evolution processes of cancer according to regression residuals network. BIBM 2021: 3713-3719 - [c47]Huan Dai, Yupei Zhang, Yue Yun, Rui An, Xuequn Shang:
VarSKD: A Variational Student Knowledge Diagnosis for Efficiently Representing Student Latent Knowledge Space. IEEE BigData 2021: 1589-1594 - [c46]Yupei Zhang, Yaya Zhou, Min Xiao, Xuequn Shang:
Comment Text Grading for Chinese Graduate Academic Dissertation Using Attention Convolutional Neural Networks. ICSAI 2021: 1-6 - [c45]Yupei Zhang, Rui An, Jiaqi Cui, Xuequn Shang:
Undergraduate Grade Prediction in Chinese Higher Education Using Convolutional Neural Networks. LAK 2021: 462-468 - [c44]Huan Dai, Yupei Zhang, Yue Yun, Xuequn Shang:
An Improved Deep Model for Knowledge Tracing and Question-Difficulty Discovery. PRICAI (2) 2021: 362-375 - 2020
- [j33]Jiajie Peng, Junya Lu, Donghee Hoh, Ayesha S. Dina, Xuequn Shang, David M. Kramer, Jin Chen:
Identifying emerging phenomenon in long temporal phenotyping experiments. Bioinform. 36(2): 568-577 (2020) - [j32]Yang Qi, Yang Guo, Huixin Jiao, Xuequn Shang:
A flexible network-based imputing-and-fusing approach towards the identification of cell types from single-cell RNA-seq data. BMC Bioinform. 21(1): 240 (2020) - [j31]Yuanke Zhong, Jing Li, Junhao He, Yiqun Gao, Jie Liu, Jingru Wang, Xuequn Shang, Jialu Hu:
Twadn: an efficient alignment algorithm based on time warping for pairwise dynamic networks. BMC Bioinform. 21-S(13): 385 (2020) - [j30]Jiajie Peng, Jingyi Li, Xuequn Shang:
A learning-based method for drug-target interaction prediction based on feature representation learning and deep neural network. BMC Bioinform. 21-S(13): 394 (2020) - [j29]Bolin Chen, Manting Yang, Li Gao, Tao Jiang, Xuequn Shang:
A functional network construction method to interpret the pathological process of colorectal cancer. Int. J. Data Min. Bioinform. 23(3): 251-264 (2020) - [j28]Samer Abdulateef, Naseer Ahmed Khan, Bolin Chen, Xuequn Shang:
Multidocument Arabic Text Summarization Based on Clustering and Word2Vec to Reduce Redundancy. Inf. 11(2): 59 (2020) - [j27]Samer Abdulateef, Naseer Ahmed Khan, Bolin Chen, Xuequn Shang:
Machine Learning Based Sentiment Text Classification for Evaluating Treatment Quality of Discharge Summary. Inf. 11(5): 281 (2020) - [j26]Yupei Zhang, Huan Dai, Yue Yun, Shuhui Liu, Andrew S. Lan, Xuequn Shang:
Meta-knowledge dictionary learning on 1-bit response data for student knowledge diagnosis. Knowl. Based Syst. 205: 106290 (2020) - [c43]Xinpeng Guo, Yanli Lu, Zhilei Yin, Xuequn Shang:
IPMM: Cancer Subtype Clustering Model Based on Multiomics Data and Pathway and Motif Information. ADMA 2020: 560-568 - [c42]Bolin Chen, Li Gao, Xuequn Shang:
A Machine Learning Based Method to Identify Differentially Expressed Genes. ICIC (2) 2020: 21-31 - [c41]Bolin Chen, Teng Wang, Xuequn Shang:
Identification and Analysis of Genes Involved in Stages of Colon Cancer. ICIC (2) 2020: 161-172
2010 – 2019
- 2019
- [j25]Jiajie Peng, Weiwei Hui, Qianqian Li, Bolin Chen, Jianye Hao, Qinghua Jiang, Xuequn Shang, Zhongyu Wei:
A learning-based framework for miRNA-disease association identification using neural networks. Bioinform. 35(21): 4364-4371 (2019) - [j24]Jialu Hu, Jingru Wang, Jianan Lin, Tianwei Liu, Yuanke Zhong, Jie Liu, Yan Zheng, Yiqun Gao, Junhao He, Xuequn Shang:
MD-SVM: a novel SVM-based algorithm for the motif discovery of transcription factor binding sites. BMC Bioinform. 20-S(7): 41-48 (2019) - [j23]Chaima Aouiche, Bolin Chen, Xuequn Shang:
Predicting stage-specific cancer related genes and their dynamic modules by integrating multiple datasets. BMC Bioinform. 20-S(7): 97-107 (2019) - [j22]Jiajie Peng, Xiaoyu Wang, Xuequn Shang:
Combining gene ontology with deep neural networks to enhance the clustering of single cell RNA-Seq data. BMC Bioinform. 20-S(8): 284:1-284:12 (2019) - [j21]Jialu Hu, Yiqun Gao, Jing Li, Yan Zheng, Jingru Wang, Xuequn Shang:
A novel algorithm based on bi-random walks to identify disease-related lncRNAs. BMC Bioinform. 20-S(18): 569:1-569:11 (2019) - [j20]Jiajie Peng, Guilin Lu, Hansheng Xue, Tao Wang, Xuequn Shang:
TS-GOEA: a web tool for tissue-specific gene set enrichment analysis based on gene ontology. BMC Bioinform. 20-S(18): 572:1-572:7 (2019) - [j19]Shiquan Sun, Yabo Chen, Yang Liu, Xuequn Shang:
A fast and efficient count-based matrix factorization method for detecting cell types from single-cell RNAseq data. BMC Syst. Biol. 13-S(2): 28:1-28:8 (2019) - [j18]Hansheng Xue, Jiajie Peng, Xuequn Shang:
Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO. BMC Syst. Biol. 13-S(2): 34:1-34:12 (2019) - [j17]Yang Guo, Xuequn Shang, Zhanhuai Li:
Identification of cancer subtypes by integrating multiple types of transcriptomics data with deep learning in breast cancer. Neurocomputing 324: 20-30 (2019) - [c40]Hansheng Xue, Jiajie Peng, Xuequn Shang:
Towards Gene Function Prediction via Multi-Networks Representation Learning. AAAI 2019: 10069-10070 - [c39]Bolin Chen, Manting Yang, Li Gao, Xuequn Shang:
Identifying functional evolution processes according to the pathological stages of colorectal cancer. BIBM 2019: 193-196 - [c38]Yuanke Zhong, Jing Li, Jie Liu, Yan Zheng, Xuequn Shang, Jialu Hu:
Deep learning enables accurate alignment of single cell RNA-seq data. BIBM 2019: 778-781 - [c37]Shiquan Sun, Yang Liu, Xuequn Shang:
Deep generative autoencoder for low-dimensional embeding extraction from single-cell RNAseq data. BIBM 2019: 1365-1372 - [c36]Jiajie Peng, Lu Han, Xuequn Shang:
A deconvolution method for predicting cell abundance based on single cell RNA-seq data. BIBM 2019: 1769-1773 - [c35]Hansheng Xue, Jiajie Peng, Jiying Li, Xuequn Shang:
Integrating Multi-Network Topology via Deep Semi-supervised Node Embedding. CIKM 2019: 2117-2120 - [c34]Yupei Zhang, Huan Dai, Yue Yun, Xuequn Shang:
Student Knowledge Diagnosis on Response Data via the Model of Sparse Factor Learning. EDM 2019 - [c33]Bolin Chen, Li Gao, Xuequn Shang:
Identifying Differentially Expressed Genes Based on Differentially Expressed Edges. ICIC (2) 2019: 105-115 - [c32]Bolin Chen, Chenfei Wang, Li Gao, Xuequn Shang:
A Flexible and Comprehensive Platform for Analyzing Gene Expression Data. IDMB 2019: 170-183 - [c31]Bolin Chen, Chaima Aouiche, Xuequn Shang:
Integrating Multiple Datasets to Discover Stage-Specific Cancer Related Genes and Stage-Specific Pathways. IWBBIO (1) 2019: 240-250 - 2018
- [j16]Jialu Hu, Yiqun Gao, Junhao He, Yan Zheng, Xuequn Shang:
WebNetCoffee: a web-based application to identify functionally conserved proteins from Multiple PPI networks. BMC Bioinform. 19(1): 422:1-422:6 (2018) - [j15]Jiajie Peng, Weiwei Hui, Xuequn Shang:
Measuring phenotype-phenotype similarity through the interactome. BMC Bioinform. 19-S(5): 65-77 (2018) - [j14]Yang Guo, Shuhui Liu, Zhanhuai Li, Xuequn Shang:
BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data. BMC Bioinform. 19-S(5): 118:1-118:13 (2018) - [j13]Jialu Hu, Yiqun Gao, Yan Zheng, Xuequn Shang:
KF-finder: identification of key factors from host-microbial networks in cervical cancer. BMC Syst. Biol. 12(4): 41-48 (2018) - [j12]Jiajie Peng, Xuanshuo Zhang, Weiwei Hui, Junya Lu, Qianqian Li, Shuhui Liu, Xuequn Shang:
Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach. BMC Syst. Biol. 12(S-2): 109-116 (2018) - [j11]Chaima Aouiche, Xuequn Shang, Bolin Chen:
Copy number variation related disease genes. Quant. Biol. 6(2): 99-112 (2018) - [c30]Bo Yang, Shuhui Liu, Shanmin Pang, Chenpai Pang, Xuequn Shang:
Deep Subspace Similarity Fusion for the Prediction of Cancer Subtypes. BIBM 2018: 566-571 - [c29]Yiqun Gao, Jialu Hu, Xuequn Shang:
Identification of lncRNA-disease association using bi-random walks. BIBM 2018: 1249-1255 - [c28]Jiajie Peng, Guilin Lu, Hansheng Xue, Tao Wang, Xuequn Shang:
TSGOE: A web tool for tissue-specific gene ontology enrichment. BIBM 2018: 1266-1269 - [c27]Jialu Hu, Junhao He, Yiqun Gao, Yan Zheng, Xuequn Shang:
NetCoffee2: A Novel Global Alignment Algorithm for Multiple PPI Networks Based on Graph Feature Vectors. ICIC (2) 2018: 241-246 - [c26]Shuhui Liu, Xuequn Shang:
Hierarchical Similarity Network Fusion for Discovering Cancer Subtypes. ISBRA 2018: 125-136 - [c25]Yupei Zhang, Shuhui Liu, Xuequn Shang, Ming Xiang:
Low-Rank Graph Regularized Sparse Coding. PRICAI (1) 2018: 177-190 - [i1]Hansheng Xue, Jiajie Peng, Xuequn Shang:
Deep Feature Learning of Multi-Network Topology for Node Classification. CoRR abs/1809.02394 (2018) - 2017
- [j10]Jiajie Peng, Qianqian Li, Xuequn Shang:
Investigations on factors influencing HPO-based semantic similarity calculation. J. Biomed. Semant. 8-S(1): 61-69 (2017) - [j9]Jiajie Peng, Honggang Wang, Junya Lu, Weiwei Hui, Yadong Wang, Xuequn Shang:
Identifying term relations cross different gene ontology categories. BMC Bioinform. 18(16): 67-74 (2017) - [j8]Jiajie Peng, Hansheng Xue, Yukai Shao, Xuequn Shang, Yadong Wang, Jin Chen:
A novel method to measure the semantic similarity of HPO terms. Int. J. Data Min. Bioinform. 17(2): 173-188 (2017) - [j7]Bo Yang, Xuequn Shang, Shanmin Pang:
Isometric hashing for image retrieval. Signal Process. Image Commun. 59: 117-130 (2017) - [c24]Jialu Hu, Yan Zheng, Xuequn Shang:
MiteFinder: A fast approach to identify miniature inverted-repeat transposable elements on a genome-wide scale. BIBM 2017: 164-168 - [c23]Yang Guo, Shuhui Liu, Zhanhuai Li, Xuequn Shang:
Towards the classification of cancer subtypes by using cascade deep forest model in gene expression data. BIBM 2017: 1664-1669 - [c22]Jiajie Peng, Weiwei Hui, Xuequn Shang:
Measuring phenotype-phenotype similarity through the interactome. BIBM 2017: 1674-1677 - [c21]Bolin Chen, Yuqiong Jin, Xuequn Shang:
Net2Image: A Network Representation Method for Identifying Cancer-Related Genes. ISBRA 2017: 337-343 - 2016
- [j6]Xuequn Shang, Yu Wang, Bolin Chen:
Identifying essential proteins based on dynamic protein-protein interaction networks and RNA-Seq datasets. Sci. China Inf. Sci. 59(7): 070106:1-070106:11 (2016) - [j5]Tao Jiang, Zhanhuai Li, Xuequn Shang, Bolin Chen, Weibang Li, Zhilei Yin:
Constrained query of order-preserving submatrix in gene expression data. Frontiers Comput. Sci. 10(6): 1052-1066 (2016) - [j4]Tao Jiang, Zhanhuai Li, Xuequn Shang, Bolin Chen, Weibang Li:
基因表达数据中局部模式的查询 (Local Pattern Query from Gene Expression Data). 计算机科学 43(7): 191-196 (2016) - [c20]Jianyu Shi, Ke Gao, Xue-Qun Shang, Siu-Ming Yiu:
LCM-DS: A novel approach of predicting drug-drug interactions for new drugs via Dempster-Shafer theory of evidence. BIBM 2016: 512-515 - [c19]Jiajie Peng, Hansheng Xue, Yukai Shao, Xuequn Shang, Yadong Wang, Jin Chen:
Measuring phenotype semantic similarity using Human Phenotype Ontology. BIBM 2016: 763-766 - [c18]Jiajie Peng, Qianqian Li, Bolin Chen, Jialu Hu, Xuequn Shang:
Analyzing factors involved in the HPO-based semantic similarity calculation. BIBM 2016: 1653-1656 - 2015
- [c17]Bolin Chen, Xuequn Shang, Min Li, Jianxin Wang, Fang-Xiang Wu:
A two-step logistic regression algorithm for identifying individual-cancer-related genes. BIBM 2015: 195-200 - 2014
- [c16]Yang Guo, Xuequn Shang, Qingping Zhu, Mingkui Huang, Zhanhuai Li:
Identification of protein complexes and functional modules in integrated PPI networks. BIBM 2014: 8-15 - 2013
- [c15]Yang Guo, Xuequn Shang, Jing Li, Zhanhuai Li:
Revealing the Causes of Dynamic Change in Protein-Protein Interaction Network. BigData Congress 2013: 189-194 - 2011
- [j3]Miao Wang, Xuequn Shang, Zhanhuai Li:
MFC: Mining Maximal Frequent Dense Subgraphs without Candidate Maintenance in Imbalanced PPI Networks. J. Softw. 6(3): 498-507 (2011) - [c14]Miao Wang, Xuequn Shang, Miao Miao, Zhanhuai Li, Wenbin Liu:
FTCluster: Efficient Mining Fault-Tolerant Biclusters in Microarray Dataset. ICDM Workshops 2011: 1075-1082 - [c13]Miao Wang, Xuequn Shang, Miao Miao, Zhanhuai Li, Wenbin Liu:
MFCluster: Mining Maximal Fault-Tolerant Constant Row Biclusters in Microarray Dataset. WAIM 2011: 181-190 - 2010
- [j2]Miao Wang, Xuequn Shang, Shaohua Zhang, Zhanhuai Li:
Efficient Mining Frequent Closed Discriminative Biclusters by Sample-Growth: The FDCluster Approach. Int. J. Knowl. Discov. Bioinform. 1(4): 69-88 (2010) - [c12]Miao Wang, Xuequn Shang, Jingni Diao, Zhanhuai Li:
WIBE: Mining Frequent Closed Patterns Without Candidate Maintenance in Microarray Dataset. DMIN 2010: 200-205 - [c11]Miao Wang, Xuequn Shang, Shaohua Zhang, Zhanhuai Li:
FDCluster: Mining Frequent Closed Discriminative Bicluster without Candidate Maintenance in Multiple Microarray Datasets. ICDM Workshops 2010: 779-786
2000 – 2009
- 2009
- [c10]Xuequn Shang, Qian Zhao, Zhanhuai Li:
Mining High-Correlation Association Rules for Inferring Gene Regulation Networks. DaWaK 2009: 244-255 - [c9]Xuequn Shang, Zhanhuai Li, Wei Li:
Mining functional associated patterns from biological network data. SAC 2009: 1488-1489 - 2008
- [c8]Miao Wang, Xuequn Shang, Zhanhuai Li:
Sequential Pattern Mining for Protein Function Prediction. ADMA 2008: 652-658 - 2007
- [j1]Xuequn Shang, Kai-Uwe Sattler:
Processing Sequential Patterns in Relational Databases. J. Data Semant. 8: 203-217 (2007) - [c7]Xuequn Shang:
A Survey of Frequent Pattern Mining for Biological Datasets. DMIN 2007: 242-248 - 2005
- [b1]Xuequn Shang:
SQL based frequent pattern mining. Otto-von-Guericke University Magdeburg, Germany, 2005, pp. 1-127 - [c6]Xuequn Shang, Kai-Uwe Sattler:
Processing Sequential Patterns in Relational Databases. DaWaK 2005: 438-447 - [c5]Xuequn Shang, Kai-Uwe Sattler:
Frequent Itemset Mining with Parallel RDBMS. PAKDD 2005: 539-544 - [c4]Xuequn Shang, Kai-Uwe Sattler:
Depth-first frequent itemset mining in relational databases. SAC 2005: 1112-1117 - 2004
- [c3]Xuequn Shang, Kai-Uwe Sattler, Ingolf Geist:
Efficient Frequent Pattern Mining in Relational Databases. LWA 2004: 84-91 - [c2]Xuequn Shang, Kai-Uwe Sattler, Ingolf Geist:
SQL based frequent pattern mining without candidate generation. SAC 2004: 618-619 - [c1]Xuequn Shang, Kai-Uwe Sattler, Ingolf Geist:
SQL Based Frequent Pattern Mining with FP-Growth. INAP/WLP 2004: 32-46
Coauthor Index
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