| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/bmcsb/JiangHWJZTLW10 |
| P6179 | Dimensions Publication ID | 1049361572 |
| P356 | DOI | 10.1186/1752-0509-4-S1-S2 |
| P932 | PMC publication ID | 2880408 |
| P698 | PubMed publication ID | 20522252 |
| P5875 | ResearchGate publication ID | 44648291 |
| P50 | author | Mingxiang Teng | Q42697106 |
| P2093 | author name string | Guohua Wang | |
| Yadong Wang | |||
| Yunlong Liu | |||
| Qinghua Jiang | |||
| Liran Juan | |||
| Tianjiao Zhang | |||
| Yangyang Hao | |||
| P2860 | cites work | Mapping gene associations in human mitochondria using clinical disease phenotypes | Q21145361 |
| Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders | Q24558589 | ||
| MicroRNA-221/222 negatively regulates estrogen receptor alpha and is associated with tamoxifen resistance in breast cancer | Q24645663 | ||
| miR-19, miR-101 and miR-130 co-regulate ATXN1 levels to potentially modulate SCA1 pathogenesis | Q24647507 | ||
| MicroRNA-221/222 confers tamoxifen resistance in breast cancer by targeting p27Kip1 | Q24648241 | ||
| miRBase: tools for microRNA genomics | Q24649872 | ||
| Truncation in CCND1 mRNA alters miR-16-1 regulation in mantle cell lymphoma | Q24655119 | ||
| Down-regulation of micro-RNA-1 (miR-1) in lung cancer. Suppression of tumorigenic property of lung cancer cells and their sensitization to doxorubicin-induced apoptosis by miR-1 | Q24655144 | ||
| miR2Disease: a manually curated database for microRNA deregulation in human disease | Q24655615 | ||
| MicroRNA-221-222 regulate the cell cycle in mast cells | Q24656557 | ||
| The human disease network | Q24678240 | ||
| Speeding disease gene discovery by sequence based candidate prioritization | Q24811442 | ||
| G2D: a tool for mining genes associated with disease | Q24813279 | ||
| Prediction of mammalian microRNA targets | Q27860498 | ||
| MicroRNA signatures in human cancers | Q27860962 | ||
| Network biology: understanding the cell's functional organization | Q27861027 | ||
| MicroRNAs: genomics, biogenesis, mechanism, and function | Q27861070 | ||
| MicroRNA expression profiles classify human cancers | Q28032481 | ||
| Tumour invasion and metastasis initiated by microRNA-10b in breast cancer | Q28131829 | ||
| The let-7 microRNA reduces tumor growth in mouse models of lung cancer | Q28272817 | ||
| The muscle-specific microRNA miR-1 regulates cardiac arrhythmogenic potential by targeting GJA1 and KCNJ2 | Q28295943 | ||
| MicroRNA-7, a homeobox D10 target, inhibits p21-activated kinase 1 and regulates its functions | Q28297593 | ||
| MicroRNA in cancer prognosis | Q28304380 | ||
| miR-133 and miR-30 regulate connective tissue growth factor: implications for a role of microRNAs in myocardial matrix remodeling | Q28304542 | ||
| The bifunctional microRNA miR-9/miR-9* regulates REST and CoREST and is downregulated in Huntington's disease | Q28305485 | ||
| MicroRNA regulation of DNA repair gene expression in hypoxic stress | Q28306694 | ||
| The role of site accessibility in microRNA target recognition | Q29547436 | ||
| A human phenome-interactome network of protein complexes implicated in genetic disorders | Q29614448 | ||
| A similarity-based method for genome-wide prediction of disease-relevant human genes | Q52030251 | ||
| Coordinated regulation of cell cycle transcripts by p53-Inducible microRNAs, miR-192 and miR-215. | Q53431796 | ||
| MicroRNA signature predicts survival and relapse in lung cancer | Q53507653 | ||
| Phenome connections | Q80615290 | ||
| Network medicine--from obesity to the "diseasome" | Q80673341 | ||
| A text-mining analysis of the human phenome | Q82627143 | ||
| Human microRNAs co-silence in well-separated groups and have different predicted essentialities | Q83161219 | ||
| Association of genes to genetically inherited diseases using data mining | Q30692445 | ||
| Analysis of protein sequence and interaction data for candidate disease gene prediction | Q31064465 | ||
| Gene prioritization through genomic data fusion | Q33242612 | ||
| The microRNAs miR-373 and miR-520c promote tumour invasion and metastasis | Q33314551 | ||
| Prediction of human disease genes by human-mouse conserved coexpression analysis | Q33325895 | ||
| An analysis of human microRNA and disease associations | Q33377048 | ||
| An integrated approach to inferring gene-disease associations in humans | Q33669063 | ||
| The modular nature of genetic diseases. | Q34597943 | ||
| Prognostic value of mature microRNA-21 and microRNA-205 overexpression in non-small cell lung cancer by quantitative real-time RT-PCR. | Q34811436 | ||
| Four miRNAs associated with aggressiveness of lymph node-negative, estrogen receptor-positive human breast cancer | Q34816422 | ||
| Genome-wide identification of genes likely to be involved in human genetic disease | Q35130251 | ||
| Network-based global inference of human disease genes | Q36713985 | ||
| A computational screen for mouse signaling pathways targeted by microRNA clusters. | Q36740718 | ||
| Computational analysis of microRNA profiles and their target genes suggests significant involvement in breast cancer antiestrogen resistance | Q37097112 | ||
| Protein networks in disease | Q37125547 | ||
| Short non-coding RNA biology and neurodegenerative disorders: novel disease targets and therapeutics | Q37134134 | ||
| A network medicine approach to human disease | Q37408792 | ||
| A computational system to select candidate genes for complex human traits | Q38516993 | ||
| Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes | Q38518470 | ||
| Walking the interactome for prioritization of candidate disease genes | Q39140568 | ||
| Genome-wide prioritization of disease genes and identification of disease-disease associations from an integrated human functional linkage network | Q42594704 | ||
| Predicting disease genes using protein-protein interactions. | Q43169919 | ||
| SUSPECTS: enabling fast and effective prioritization of positional candidates | Q47399301 | ||
| P275 | copyright license | Creative Commons Attribution 2.0 Generic | Q19125117 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P921 | main subject | microRNA | Q310899 |
| prioritization | Q11888847 | ||
| P304 | page(s) | S2 | |
| P577 | publication date | 2010-05-28 | |
| P1433 | published in | BMC Systems Biology | Q4835949 |
| P1476 | title | Prioritization of disease microRNAs through a human phenome-microRNAome network | |
| P478 | volume | 4 Suppl 1 |
| Q33766560 | 2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research |
| Q36077575 | A Comprehensive Evaluation of Disease Phenotype Networks for Gene Prioritization |
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| Q64230417 | A Novel Neighborhood-Based Computational Model for Potential MiRNA-Disease Association Prediction |
| Q50421175 | A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network |
| Q45334190 | A deep ensemble model to predict miRNA-disease association |
| Q60045684 | A heterogeneous label propagation approach to explore the potential associations between miRNA and disease |
| Q28652746 | A miRNA-driven inference model to construct potential drug-disease associations for drug repositioning |
| Q47316976 | A non-negative matrix factorization based method for predicting disease-associated miRNAs in miRNA-disease bilayer network |
| Q38377228 | A novel computational model based on super-disease and miRNA for potential miRNA-disease association prediction |
| Q50048914 | A novel method for identifying potential disease-related miRNAs via a disease-miRNA-target heterogeneous network |
| Q50854439 | A novel method of predicting microRNA-disease associations based on microRNA, disease, gene and environment factor networks. |
| Q60044750 | A novel semi-supervised model for miRNA-disease association prediction based on [Formula: see text]-norm graph |
| Q33556392 | A statistically inferred microRNA network identifies breast cancer target miR-940 as an actin cytoskeleton regulator |
| Q64096900 | Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs |
| Q91650416 | An improved random forest-based computational model for predicting novel miRNA-disease associations |
| Q95272488 | BHCMDA: A New Biased Heat Conduction Based Method for Potential MiRNA-Disease Association Prediction |
| Q64084852 | Bipartite Heterogeneous Network Method Based on Co-neighbor for MiRNA-Disease Association Prediction |
| Q37973492 | Computational approaches to disease-gene prediction: rationale, classification and successes. |
| Q41709384 | Computational prediction of human disease-related microRNAs by path-based random walk |
| Q39100263 | Construction of a lncRNA-PCG bipartite network and identification of cancer-related lncRNAs: a case study in prostate cancer |
| Q36322428 | Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite |
| Q38600495 | DRMDA: deep representations-based miRNA-disease association prediction. |
| Q60949449 | Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs |
| Q47172264 | EGBMMDA: Extreme Gradient Boosting Machine for MiRNA-Disease Association prediction |
| Q52331347 | ELLPMDA: Ensemble Learning and Link Prediction for miRNA-Disease Association prediction. |
| Q35752431 | Enrichment Analysis Identifies Functional MicroRNA-Disease Associations in Humans |
| Q92072526 | Ensemble of decision tree reveals potential miRNA-disease associations |
| Q33594058 | Establishing reliable miRNA-cancer association network based on text-mining method |
| Q64070811 | FCMDAP: using miRNA family and cluster information to improve the prediction accuracy of disease related miRNAs |
| Q60923483 | FKL-Spa-LapRLS: an accurate method for identifying human microRNA-disease association |
| Q60923573 | FMSM: a novel computational model for predicting potential miRNA biomarkers for various human diseases |
| Q47224473 | GIMDA: Graphlet interaction-based MiRNA-disease association prediction. |
| Q91659524 | GLNMDA: a novel method for miRNA-disease association prediction based on global linear neighborhoods |
| Q52668402 | GRMDA: Graph Regression for MiRNA-Disease Association Prediction |
| Q34123385 | Gene prioritization for livestock diseases by data integration |
| Q52565466 | Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA-Disease Association |
| Q89763259 | Graph regularized L2,1-nonnegative matrix factorization for miRNA-disease association prediction |
| Q37662214 | HGIMDA: Heterogeneous graph inference for miRNA-disease association prediction |
| Q52568068 | HNMDA: heterogeneous network-based miRNA-disease association prediction |
| Q99712146 | Heterogeneous Graph Convolutional Networks and Matrix Completion for miRNA-Disease Association Prediction |
| Q35775025 | How to build personalized multi-omics comorbidity profiles |
| Q92539484 | Identifying Potential miRNAs-Disease Associations With Probability Matrix Factorization |
| Q58797269 | Identifying and Exploiting Potential miRNA-Disease Associations With Neighborhood Regularized Logistic Matrix Factorization |
| Q50909253 | Identifying human microRNA-disease associations by a new diffusion-based method |
| Q33920938 | Improved low-rank matrix recovery method for predicting miRNA-disease association |
| Q31150011 | Improved method for prioritization of disease associated lncRNAs based on ceRNA theory and functional genomics data |
| Q90668982 | Inferring Disease-Associated MicroRNAs Using Semi-supervised Multi-Label Graph Convolutional Networks |
| Q64121783 | Inferring microRNA-disease association by hybrid recommendation algorithm and unbalanced bi-random walk on heterogeneous network |
| Q34854544 | Inferring potential microRNA-microRNA associations based on targeting propensity and connectivity in the context of protein interaction network |
| Q92210643 | Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks |
| Q61807715 | Integrating random walk and binary regression to identify novel miRNA-disease association |
| Q31043232 | Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations |
| Q38522719 | Integrative approaches for predicting microRNA function and prioritizing disease-related microRNA using biological interaction networks |
| Q49348773 | Investigations on factors influencing HPO-based semantic similarity calculation |
| Q59804717 | LLCMDA: A Novel Method for Predicting miRNA Gene and Disease Relationship Based on Locality-Constrained Linear Coding |
| Q64114766 | LMTRDA: Using logistic model tree to predict MiRNA-disease associations by fusing multi-source information of sequences and similarities |
| Q47238496 | LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction |
| Q37387324 | Large-scale identification of adverse drug reaction-related proteins through a random walk model |
| Q37710699 | Large-scale prediction of microRNA-disease associations by combinatorial prioritization algorithm |
| Q64923416 | MCLPMDA: A novel method for miRNA-disease association prediction based on matrix completion and label propagation. |
| Q33591474 | MCMDA: Matrix completion for MiRNA-disease association prediction |
| Q60960988 | MDA-SKF: Similarity Kernel Fusion for Accurately Discovering miRNA-Disease Association |
| Q58704945 | MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction |
| Q47097674 | MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA-disease association prediction |
| Q92504718 | MLMDA: a machine learning approach to predict and validate MicroRNA-disease associations by integrating of heterogenous information sources |
| Q95272494 | MSFSP: A Novel miRNA-Disease Association Prediction Model by Federating Multiple-Similarities Fusion and Space Projection |
| Q28085741 | Mechanisms of microRNA turnover |
| Q47426585 | NARRMDA: negative-aware and rating-based recommendation algorithm for miRNA-disease association prediction |
| Q54978542 | NDAMDA: Network distance analysis for MiRNA-disease association prediction. |
| Q92993003 | NPCMF: Nearest Profile-based Collaborative Matrix Factorization method for predicting miRNA-disease associations |
| Q38392855 | NTSMDA: prediction of miRNA-disease associations by integrating network topological similarity |
| Q37363891 | Network Consistency Projection for Human miRNA-Disease Associations Inference |
| Q59136744 | Novel Human miRNA-Disease Association Inference Based on Random Forest |
| Q50724304 | Novel human lncRNA-disease association inference based on lncRNA expression profiles |
| Q36322043 | PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction |
| Q64068987 | PMAMCA: prediction of microRNA-disease association utilizing a matrix completion approach |
| Q47114178 | PRMDA: personalized recommendation-based MiRNA-disease association prediction |
| Q92344177 | Potential miRNA-disease association prediction based on kernelized Bayesian matrix factorization |
| Q64117739 | Predicting MiRNA-Disease Association by Latent Feature Extraction with Positive Samples |
| Q36280834 | Predicting disease-related genes using integrated biomedical networks. |
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| Q36953740 | Prediction of miRNA-disease associations with a vector space model |
| Q55235106 | Prediction of microRNA-disease associations based on distance correlation set. |
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| Q92237005 | RCMF: a robust collaborative matrix factorization method to predict miRNA-disease associations |
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