Related references
Note: Only part of the references are listed.Neural inductive matrix completion with graph convolutional networks for miRNA-disease association prediction
Jin Li et al.
BIOINFORMATICS (2020)
Predicting miRNA-disease association from heterogeneous information network with GraRep embedding model
Bo-Ya Ji et al.
SCIENTIFIC REPORTS (2020)
Squeeze-and-Excitation Networks
Jie Hu et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2020)
A learning-based framework for miRNA-disease association identification using neural networks
Jiajie Peng et al.
BIOINFORMATICS (2019)
Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs
Cheng Liang et al.
PLOS COMPUTATIONAL BIOLOGY (2019)
HMDD v3.0: a database for experimentally supported human microRNA-disease associations
Zhou Huang et al.
NUCLEIC ACIDS RESEARCH (2019)
MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional Networks
Mahsa Ghorbani et al.
PROCEEDINGS OF THE 2019 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2019) (2019)
Benchmark of computational methods for predicting microRNA-disease associations
Zhou Huang et al.
GENOME BIOLOGY (2019)
Modeling polypharmacy side effects with graph convolutional networks
Marinka Zitnik et al.
BIOINFORMATICS (2018)
Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs
Ping Xuan et al.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2018)
DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants
Janet Pinero et al.
NUCLEIC ACIDS RESEARCH (2017)
The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible
Damian Szklarczyk et al.
NUCLEIC ACIDS RESEARCH (2017)
MCMDA: Matrix completion for MiRNA-disease association prediction
Jian-Qiang Li et al.
ONCOTARGET (2017)
PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction
Zhu-Hong You et al.
PLOS COMPUTATIONAL BIOLOGY (2017)
ILNCSIM: improved lncRNA functional similarity calculation model
Yu-An Huang et al.
ONCOTARGET (2016)
WBSMDA: Within and Between Score for MiRNA-Disease Association prediction
Xing Chen et al.
SCIENTIFIC REPORTS (2016)
miRWalk2.0: a comprehensive atlas of microRNA-target interactions
Harsh Dweep et al.
NATURE METHODS (2015)
Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology
Aaron J. Masino et al.
BMC BIOINFORMATICS (2014)
Semi-supervised learning for potential human microRNA-disease associations inference
Xing Chen et al.
SCIENTIFIC REPORTS (2014)
Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes
Hongbo Shi et al.
BMC SYSTEMS BIOLOGY (2013)
Prediction of microRNAs Associated with Human Diseases Based on Weighted k Most Similar Neighbors
Ping Xuan et al.
PLOS ONE (2013)
RWRMDA: predicting novel human microRNA-disease associations
Xing Chen et al.
MOLECULAR BIOSYSTEMS (2012)
Breast cancer signatures for invasiveness and prognosis defined by deep sequencing of microRNA
Stefano Volinia et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2012)
Gaussian interaction profile kernels for predicting drug-target interaction
Twan van Laarhoven et al.
BIOINFORMATICS (2011)
Prioritization of disease microRNAs through a human phenome-microRNAome network
Qinghua Jiang et al.
BMC SYSTEMS BIOLOGY (2010)
The Human Phenotype Ontology: A Tool for Annotating and Analyzing Human Hereditary Disease
Peter N. Robinson et al.
AMERICAN JOURNAL OF HUMAN GENETICS (2008)
A microRNA feedback circuit in midbrain dopamine neurons
Jongpil Kim et al.
SCIENCE (2007)
Share Paper
