DeepMiR2GO: Inferring Functions of Human MicroRNAs Using a Deep Multi-Label Classification Model.
Int J Mol Sci
; 20(23)2019 Nov 30.
Article
em En
| MEDLINE
| ID: mdl-31801264
ABSTRACT
MicroRNAs (miRNAs) are a highly abundant collection of functional non-coding RNAs involved in cellular regulation and various complex human diseases. Although a large number of miRNAs have been identified, most of their physiological functions remain unknown. Computational methods play a vital role in exploring the potential functions of miRNAs. Here, we present DeepMiR2GO, a tool for integrating miRNAs, proteins and diseases, to predict the gene ontology (GO) functions based on multiple deep neuro-symbolic models. DeepMiR2GO starts by integrating the miRNA co-expression network, protein-protein interaction (PPI) network, disease phenotype similarity network, and interactions or associations among them into a global heterogeneous network. Then, it employs an efficient graph embedding strategy to learn potential network representations of the global heterogeneous network as the topological features. Finally, a deep multi-label classification network based on multiple neuro-symbolic models is built and used to annotate the GO terms of miRNAs. The predicted results demonstrate that DeepMiR2GO performs significantly better than other state-of-the-art approaches in terms of precision, recall, and maximum F-measure.
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Base de dados:
MEDLINE
Assunto principal:
Esquizofrenia
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Doenças Cardiovasculares
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Redes Neurais de Computação
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MicroRNAs
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Neoplasias
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article