MiRNA-disease association prediction via hypergraph learning based on high-dimensionality features
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Chun-Hou Zheng | Jian-Cheng Ni | Yu-Tian Wang | Qing-Wen Wu | Zhen Gao | C. Zheng | Yutian Wang | Jiancheng Ni | Zhen Gao | Qing-Wen Wu
[1] Hong Yan,et al. EmDL: Extracting miRNA-Drug Interactions from Literature , 2019, TCBB.
[2] M. Kye,et al. The role of miRNA in motor neuron disease , 2014, Front. Cell. Neurosci..
[3] Xing Chen,et al. MicroRNAs and complex diseases: from experimental results to computational models , 2019, Briefings Bioinform..
[4] M. Byrom,et al. Antisense inhibition of human miRNAs and indications for an involvement of miRNA in cell growth and apoptosis , 2005, Nucleic acids research.
[5] Cheng Liang,et al. Predicting MicroRNA-Disease Associations Using Kronecker Regularized Least Squares Based on Heterogeneous Omics Data , 2017, IEEE Access.
[6] Xing-Ming Zhao,et al. Integrative analysis of mutational and transcriptional profiles reveals driver mutations of metastatic breast cancers , 2016, Cell Discovery.
[7] Changning Liu,et al. dbDEMC: a database of differentially expressed miRNAs in human cancers , 2010, BMC Genomics.
[8] Yadong Wang,et al. Prioritization of disease microRNAs through a human phenome-microRNAome network , 2010, BMC Systems Biology.
[9] L. Gomella,et al. Prostate Cancer Statistics: Anything You Want Them To Be. , 2017, The Canadian journal of urology.
[10] Andrew Feber,et al. MicroRNA expression profiles of esophageal cancer. , 2008, The Journal of thoracic and cardiovascular surgery.
[11] A. Jemal,et al. Global cancer statistics, 2012 , 2015, CA: a cancer journal for clinicians.
[12] Na-Na Guan,et al. GRMDA: Graph Regression for MiRNA-Disease Association Prediction , 2018, Front. Physiol..
[13] Xing Chen,et al. LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction , 2017, PLoS Comput. Biol..
[14] Xing-Ming Zhao,et al. Identifying cancer-related microRNAs based on gene expression data , 2015, Bioinform..
[15] James W Jacobson,et al. MicroRNA: Potential for Cancer Detection, Diagnosis, and Prognosis. , 2007, Cancer research.
[16] Publisher's Note , 2018, Anaesthesia.
[17] T. Hibi,et al. MicroRNAs in Hepatobiliary and Pancreatic Cancers , 2011, Front. Gene..
[18] Na-Na Guan,et al. Predicting miRNA‐disease association based on inductive matrix completion , 2018, Bioinform..
[19] Lei Wang,et al. BNPMDA: Bipartite Network Projection for MiRNA–Disease Association prediction , 2018, Bioinform..
[20] Xing-Ming Zhao,et al. Identifying Disease Associated miRNAs Based on Protein Domains , 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[21] Xiangxiang Zeng,et al. Inferring MicroRNA-Disease Associations by Random Walk on a Heterogeneous Network with Multiple Data Sources , 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[22] D. Bartel. MicroRNAs: Target Recognition and Regulatory Functions , 2009, Cell.
[23] Chenggang Clarence Yan,et al. Predict MiRNA-Disease Association with Collaborative Filtering , 2018, Neuroinformatics.
[24] Xing Chen,et al. HGIMDA: Heterogeneous graph inference for miRNA-disease association prediction , 2016, Oncotarget.
[25] Lei Wang,et al. An efficient approach based on multi-sources information to predict circRNA-disease associations using deep convolutional neural network , 2019, Bioinform..
[26] Xing Chen,et al. PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction , 2017, PLoS Comput. Biol..
[27] Chenggang Clarence Yan,et al. SACMDA: MiRNA-Disease Association Prediction with Short Acyclic Connections in Heterogeneous Graph , 2018, Neuroinformatics.
[28] Yue Gao,et al. Inductive Multi-Hypergraph Learning and Its Application on View-Based 3D Object Classification , 2018, IEEE Transactions on Image Processing.
[29] Dong Wang,et al. Inferring the human microRNA functional similarity and functional network based on microRNA-associated diseases , 2010, Bioinform..
[30] A. Jemal,et al. Breast cancer statistics, 2015: Convergence of incidence rates between black and white women , 2016, CA: a cancer journal for clinicians.
[31] Hong Zhu,et al. MiR-130b plays an oncogenic role by repressing PTEN expression in esophageal squamous cell carcinoma cells , 2015, BMC Cancer.
[32] Xing Chen,et al. HAMDA: Hybrid Approach for MiRNA-Disease Association prediction , 2017, J. Biomed. Informatics.
[33] Xing Chen,et al. EGBMMDA: Extreme Gradient Boosting Machine for MiRNA-Disease Association prediction , 2018, Cell Death & Disease.
[34] Xing-Ming Zhao,et al. Predicting drug-disease associations with heterogeneous network embedding. , 2019, Chaos.
[35] Yun Xiao,et al. Prioritizing Candidate Disease miRNAs by Topological Features in the miRNA Target–Dysregulated Network: Case Study of Prostate Cancer , 2011, Molecular Cancer Therapeutics.
[36] Danish Sayed,et al. MicroRNAs in development and disease. , 2011, Physiological reviews.
[37] Xing Chen,et al. RWRMDA: predicting novel human microRNA-disease associations. , 2012, Molecular bioSystems.
[38] R. Shivdasani. MicroRNAs: regulators of gene expression and cell differentiation. , 2006, Blood.
[39] W. Cho. MicroRNAs: potential biomarkers for cancer diagnosis, prognosis and targets for therapy. , 2010, The international journal of biochemistry & cell biology.
[40] Wei-Dong Chen,et al. Interplay of miRNAs and Canonical Wnt Signaling Pathway in Hepatocellular Carcinoma , 2018, Front. Pharmacol..
[41] Q. Cui,et al. An Analysis of Human MicroRNA and Disease Associations , 2008, PloS one.
[42] Na-Na Guan,et al. GIMDA: Graphlet interaction‐based MiRNA‐disease association prediction , 2017, Journal of cellular and molecular medicine.
[43] Qionghai Dai,et al. RBMMMDA: predicting multiple types of disease-microRNA associations , 2015, Scientific Reports.
[44] Yang Li,et al. HMDD v2.0: a database for experimentally supported human microRNA and disease associations , 2013, Nucleic Acids Res..
[45] Xing Chen,et al. MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction , 2018, PLoS Comput. Biol..
[46] Xing Chen,et al. Ensemble of decision tree reveals potential miRNA-disease associations , 2019, PLoS Comput. Biol..
[47] Xantha Karp,et al. Encountering MicroRNAs in Cell Fate Signaling , 2005, Science.
[48] Xia Li,et al. Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes , 2013, BMC Systems Biology.
[49] Elena Marchiori,et al. Gaussian interaction profile kernels for predicting drug-target interaction , 2011, Bioinform..
[50] Cheng Liang,et al. A graph regularized non-negative matrix factorization method for identifying microRNA-disease associations , 2018, Bioinform..
[51] Xing Chen,et al. Semi-supervised learning for potential human microRNA-disease associations inference , 2014, Scientific Reports.
[52] Yadong Wang,et al. miR2Disease: a manually curated database for microRNA deregulation in human disease , 2008, Nucleic Acids Res..
[53] Yajie Wang,et al. Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis , 2019, Front. Cell. Infect. Microbiol..
[54] Bernhard Schölkopf,et al. Learning with Hypergraphs: Clustering, Classification, and Embedding , 2006, NIPS.
[55] Frank J. Slack,et al. Aberrant Regulation and Function of MicroRNAs in Cancer , 2014, Current Biology.
[56] A. Jemal,et al. Global cancer statistics , 2011, CA: a cancer journal for clinicians.