Novel human lncRNA-disease association inference based on lncRNA expression profiles. - Xing Chen 001; Guiying Yan (Bioinform., 2013)

LncRNADisease: a database for long-non-coding RNA-associated diseases. - Geng Chen; Ziyun Wang; Dongqing Wang; Chengxiang Qiu; Mingxi Liu; Xing Chen 001; Qipeng Zhang; Guiying Yan; Qinghua Cui (Nucleic Acids Res., 2013)

Large scale image understanding with non-convex multi-task learning. - Liang Li 003; Chenggang Yan 001; Xing Chen 001; Shuqiang Jiang; Seungmin Rho; Jian Yin 003; Baochen Jiang; Qingming Huang (GAMENETS, 2014)

Super-λ Connectivity of Bipartite Graphs. - Xing Chen 001; Wei Xiong; Jixiang Meng (Ars Comb., 2014)

Drug-target interaction prediction: databases, web servers and computational models. - Xing Chen 001; Chenggang Clarence Yan; Xiaotian Zhang; Xu Zhang 028; Feng Dai; Jian Yin 003; Yongdong Zhang 001 (Briefings Bioinform., 2016)

Sequence-based prediction of protein-protein interactions using weighted sparse representation model combined with global encoding. - Yu-An Huang; Zhu-Hong You; Xing Chen 001; Keith C. C. Chan; Xin Luo 001 (BMC Bioinform., 2016)

Improved protein-protein interactions prediction via weighted sparse representation model combining continuous wavelet descriptor and PseAA composition. - Yu-An Huang; Zhu-Hong You; Xing Chen 001; Guiying Yan (BMC Syst. Biol., 2016)

Stochastic modeling suggests that noise reduces differentiation efficiency by inducing a heterogeneous drug response in glioma differentiation therapy. - Xiaoqiang Sun; Jiajun Zhang 008; Qi Zhao; Xing Chen 001; Wenbo Zhu; Guangmei Yan; Tianshou Zhou (BMC Syst. Biol., 2016)

Construction of reliable protein-protein interaction networks using weighted sparse representation based classifier with pseudo substitution matrix representation features. - Yu-An Huang; Zhu-Hong You; Xiao Li 007; Xing Chen 001; Pengwei Hu 001; Shuai Li 002; Xin Luo 001 (Neurocomputing, 2016)

Distributed image understanding with semantic dictionary and semantic expansion. - Liang Li 003; Chenggang Clarence Yan; Xing Chen 001; Chunjie Zhang; Jian Yin 003; Baochen Jiang; Qingming Huang (Neurocomputing, 2016)

NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning. - Xing Chen 001; Biao Ren; Ming Chen; Quanxin Wang; Lixin Zhang 006; Guiying Yan (PLoS Comput. Biol., 2016)

Computational Methods for the Prediction of Drug-Target Interactions from Drug Fingerprints and Protein Sequences by Stacked Auto-Encoder Deep Neural Network. - Lei Wang 121; Zhu-Hong You; Xing Chen 001; Shixiong Xia; Feng Liu 039; Xin Yan; Yong Zhou 003 (ISBRA, 2017)

Long non-coding RNAs and complex diseases: from experimental results to computational models. - Xing Chen 001; Chenggang Clarence Yan; Xu Zhang 028; Zhu-Hong You (Briefings Bioinform., 2017)

NRDTD: a database for clinically or experimentally supported non-coding RNAs and drug targets associations. - Xing Chen 001; Ya-Zhou Sun; De-Hong Zhang; Jian-Qiang Li 001; Guiying Yan; Ji-Yong An; Zhu-Hong You (Database J. Biol. Databases Curation, 2017)

DLREFD: a database providing associations of long non-coding RNAs, environmental factors and phenotypes. - Ya-Zhou Sun; De-Hong Zhang; Zhong Ming 001; Jian-Qiang Li 001; Xing Chen 001 (Database J. Biol. Databases Curation, 2017)

HAMDA: Hybrid Approach for MiRNA-Disease Association prediction. - Xing Chen 001; Ya-Wei Niu; Guanghui Wang 002; Guiying Yan (J. Biomed. Informatics, 2017)

LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction. - Xing Chen 001; Li Huang (PLoS Comput. Biol., 2017)

PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction. - Zhu-Hong You; Zhi-an Huang; Zexuan Zhu; Guiying Yan; Zheng-Wei Li 001; Zhenkun Wen; Xing Chen 001 (PLoS Comput. Biol., 2017)

PSPEL: In Silico Prediction of Self-Interacting Proteins from Amino Acids Sequences Using Ensemble Learning. - Jian-Qiang Li 001; Zhu-Hong You; Xiao Li 007; Zhong Ming 001; Xing Chen 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2017)

Fault Tolerance of λ-Optimal Graphs. - Xing Chen 001; Wei Xiong; Jixiang Meng (Ars Comb., 2018)

A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases. - Xing Chen 001; Yu-An Huang; Zhu-Hong You; Guiying Yan; Xuesong Wang 001 (Bioinform., 2018)

Predicting miRNA-disease association based on inductive matrix completion. - Xing Chen 001; Lei Wang 121; Jia Qu; Na-Na Guan; Jian-Qiang Li 001 (Bioinform., 2018)

BNPMDA: Bipartite Network Projection for MiRNA-Disease Association prediction. - Xing Chen 001; Di Xie; Lei Wang 121; Qi Zhao; Zhu-Hong You; Hongsheng Liu 001 (Bioinform., 2018)

DroidDet: Effective and robust detection of android malware using static analysis along with rotation forest model. - Hui-Juan Zhu; Zhu-Hong You; Zexuan Zhu; Wei-Lei Shi; Xing Chen 001; Li Cheng (Neurocomputing, 2018)

A Computational-Based Method for Predicting Drug-Target Interactions by Using Stacked Autoencoder Deep Neural Network. - Lei Wang 121; Zhu-Hong You; Xing Chen 001; Shixiong Xia; Feng Liu 039; Xin Yan; Yong Zhou 003; Kejian Song (J. Comput. Biol., 2018)

Inferring potential small molecule-miRNA association based on triple layer heterogeneous network. - Jia Qu; Xing Chen 001; Ya-Zhou Sun; Jian-Qiang Li 001; Zhong Ming 001 (J. Cheminformatics, 2018)

MeT-DB V2.0: elucidating context-specific functions of N6-methyl-adenosine methyltranscriptome. - Hui Liu 024; Huaizhi Wang; Zhen Wei; Songyao Zhang; Gang Hua 002; Shao-Wu Zhang 001; Lin Zhang 015; Shou-Jiang Gao; Jia Meng 001; Xing Chen 001; Yufei Huang 001 (Nucleic Acids Res., 2018)

MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction. - Xing Chen 001; Jun Yin; Jia Qu; Li Huang (PLoS Comput. Biol., 2018)

An improved efficient rotation forest algorithm to predict the interactions among proteins. - Lei Wang 121; Zhu-Hong You; Shixiong Xia; Xing Chen 001; Xin Yan; Yong Zhou 003; Feng Liu 039 (Soft Comput., 2018)

RNA methylation and diseases: experimental results, databases, Web servers and computational models. - Xing Chen 001; Ya-Zhou Sun; Hui Liu 024; Lin Zhang 015; Jian-Qiang Li 001; Jia Meng 001 (Briefings Bioinform., 2019)

MicroRNAs and complex diseases: from experimental results to computational models. - Xing Chen 001; Di Xie; Qi Zhao; Zhu-Hong You (Briefings Bioinform., 2019)

Adaptive boosting-based computational model for predicting potential miRNA-disease associations. - Yan Zhao; Xing Chen 001; Jun Yin (Bioinform., 2019)

A Unified Framework for the Prediction of Small Molecule-MicroRNA Association Based on Cross-Layer Dependency Inference on Multilayered Networks. - Chun-Chun Wang; Xing Chen 001 (J. Chem. Inf. Model., 2019)

RFSMMA: A New Computational Model to Identify and Prioritize Potential Small Molecule-MiRNA Associations. - Chun-Chun Wang; Xing Chen 001; Jia Qu; Ya-Zhou Sun; Jian-Qiang Li 001 (J. Chem. Inf. Model., 2019)

Prediction of potential miRNA-disease associations using matrix decomposition and label propagation. - Jia Qu; Xing Chen 001; Jun Yin; Yan Zhao; Zheng-Wei Li 001 (Knowl. Based Syst., 2019)

Ensemble of decision tree reveals potential miRNA-disease associations. - Xing Chen 001; Chi-Chi Zhu; Jun Yin (PLoS Comput. Biol., 2019)

LMTRDA: Using logistic model tree to predict MiRNA-disease associations by fusing multi-source information of sequences and similarities. - Lei Wang 121; Zhu-Hong You; Xing Chen 001; Yang-Ming Li; Ya-Nan Dong; Li-Ping Li 003; Kai Zheng 020 (PLoS Comput. Biol., 2019)

Integrating random walk and binary regression to identify novel miRNA-disease association. - Ya-Wei Niu; Guanghui Wang 002; Gui-Ying Yan; Xing Chen 001 (BMC Bioinform., 2019)

MicroRNA-small molecule association identification: from experimental results to computational models. - Xing Chen 001; Na-Na Guan; Ya-Zhou Sun; Jian-Qiang Li 001; Jia Qu (Briefings Bioinform., 2020)

Deep-belief network for predicting potential miRNA-disease associations. - Xing Chen 001; Tian-Hao Li; Yan Zhao; Chun-Chun Wang; Chi-Chi Zhu (Briefings Bioinform., 2021)

Predicting potential small molecule-miRNA associations based on bounded nuclear norm regularization. - Xing Chen 001; Chi Zhou; Chun-Chun Wang; Yan Zhao (Briefings Bioinform., 2021)

Circular RNAs and complex diseases: from experimental results to computational models. - Chun-Chun Wang; Chendi Han; Qi Zhao; Xing Chen 001 (Briefings Bioinform., 2021)

Drug-pathway association prediction: from experimental results to computational models. - Chun-Chun Wang; Yan Zhao; Xing Chen 001 (Briefings Bioinform., 2021)

Microbes and complex diseases: from experimental results to computational models. - Yan Zhao; Chun-Chun Wang; Xing Chen 001 (Briefings Bioinform., 2021)

Identification of miRNA-disease associations via multiple information integration with Bayesian ranking. - Chi-Chi Zhu; Chun-Chun Wang; Yan Zhao; Mingcheng Zuo; Xing Chen 001 (Briefings Bioinform., 2021)

A deep learning-based unsupervised learning method for spatially resolved transcriptomic data analysist. - Lihong Peng; Xianzhi He; Li Zhang; Xinhuai Peng; Yuankang Lu; Zejun Li; Xing Chen 001 (BIBM, 2022)

Analyses of cell-to-cell communication combining a heterogeneous deep ensemble framework and scoring approaches from single-cell RNA sequencing data. - Lihong Peng; Ruya Yuan; Chendi Han; Jingwei Tan; Zhao Wang; Min Chen 003; Xing Chen 001 (BIBM, 2022)

Computational model for ncRNA research. - Xing Chen 001; Li Huang (Briefings Bioinform., 2022)

Updated review of advances in microRNAs and complex diseases: taxonomy, trends and challenges of computational models. - Li Huang; Li Zhang; Xing Chen 001 (Briefings Bioinform., 2022)

Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion. - Li Huang; Li Zhang; Xing Chen 001 (Briefings Bioinform., 2022)

Updated review of advances in microRNAs and complex diseases: towards systematic evaluation of computational models. - Li Huang; Li Zhang; Xing Chen 001 (Briefings Bioinform., 2022)

Prediction of potential miRNA-disease associations based on stacked autoencoder. - Chun-Chun Wang; Tian-Hao Li; Li Huang; Xing Chen 001 (Briefings Bioinform., 2022)

Dual-Network Collaborative Matrix Factorization for predicting small molecule-miRNA associations. - Shu-Hao Wang; Chun-Chun Wang; Li Huang; Lian-Ying Miao; Xing Chen 001 (Briefings Bioinform., 2022)

Ensemble of kernel ridge regression-based small molecule-miRNA association prediction in human disease. - Chun-Chun Wang; Chi-Chi Zhu; Xing Chen 001 (Briefings Bioinform., 2022)

Predicting drug-target binding affinity through molecule representation block based on multi-head attention and skip connection. - Li Zhang; Chun-Chun Wang; Xing Chen 001 (Briefings Bioinform., 2022)

Computational model for disease research. - Xing Chen 001; Li Huang (Briefings Bioinform., 2023)

SNRMPACDC: computational model focused on Siamese network and random matrix projection for anticancer synergistic drug combination prediction. - Tian-Hao Li; Chun-Chun Wang; Li Zhang; Xing Chen 001 (Briefings Bioinform., 2023)

MCFF-MTDDI: multi-channel feature fusion for multi-typed drug-drug interaction prediction. - Chen-Di Han; Chun-Chun Wang; Li Huang; Xing Chen 001 (Briefings Bioinform., 2023)

Deciphering ligand-receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data. - Lihong Peng; Jingwei Tan; Wei Xiong; Li Zhang; Zhao Wang; Ruya Yuan; Zejun Li; Xing Chen 001 (Comput. Biol. Medicine, 2023)

GPCNDTA: Prediction of drug-target binding affinity through cross-attention networks augmented with graph features and pharmacophores. - Li Zhang; Chun-Chun Wang; Yong Zhang; Xing Chen 001 (Comput. Biol. Medicine, 2023)

Computational model for drug research. - Xing Chen 001; Li Huang (Briefings Bioinform., 2024)

Drug-drug interaction prediction: databases, web servers and computational models. - Yan Zhao; Jun Yin; Li Zhang; Yong Zhang; Xing Chen 001 (Briefings Bioinform., 2024)

Identifying potential ligand-receptor interactions based on gradient boosted neural network and interpretable boosting machine for intercellular communication analysis. - Lihong Peng; Pengfei Gao; Wei Xiong; Zejun Li; Xing Chen 001 (Comput. Biol. Medicine, 2024)

RFEM: A framework for essential microRNA identification in mice based on rotation forest and multiple feature fusion. - Shu-Hao Wang; Yan Zhao; Chun-Chun Wang; Fei Chu; Lian-Ying Miao; Li Zhang; Linlin Zhuo; Xing Chen 001 (Comput. Biol. Medicine, 2024)

CellDialog: A Computational Framework for Ligand-Receptor-Mediated Cell-Cell Communication Analysis. - Lihong Peng; Wei Xiong; Chendi Han; Zejun Li; Xing Chen 001 (IEEE J. Biomed. Health Informatics, 2024)

Predicting cell-cell communication by combining heterogeneous ensemble deep learning and weighted geometric mean. - Lihong Peng; Longlong Liu; Liangliang Huang; Zongzheng Bai; Min Chen 028; Xing Chen 001 (Appl. Soft Comput., 2025)

DTI-MvSCA: An Anti-Over-Smoothing Multi-View Framework With Negative Sample Selection for Predicting Drug-Target Interactions. - Lihong Peng; Zongzheng Bai; Longlong Liu; Long Yang; Xin Liu 116; Min Chen 028; Xing Chen 001 (IEEE J. Biomed. Health Informatics, 2025)

Guest Editorial:Application of Computational Techniques in Drug Discovery and Disease Treatment. - Xing Chen 001; Qi Zhao (IEEE J. Biomed. Health Informatics, 2025)