Journal
FRONTIERS IN GENETICS
Volume 10, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2019.00003
Keywords
miRNA function annotation; miRNA co-expression; global heterogeneous network; latent representations; multi-classification
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Funding
- National Natural Science Foundation of China [61672541]
- Natural Science Foundation of Hunan Province [2017JJ3412]
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MicroRNAs (miRNAs) have been demonstrated to play significant biological roles in many human biological processes. Inferring the functions of miRNAs is an important strategy for understanding disease pathogenesis at the molecular level. In this paper, we propose an integrated model, PmiRGO, to infer the gene ontology (GO) functions of miRNAs by integrating multiple data sources, including the expression profiles of miRNAs, miRNA-target interactions, and protein-protein interactions (PPI). PmiRGO starts by building a global network consisting of three networks. Then, it employs DeepWalk to learn latent representations as network features of the global heterogeneous network. Finally, the SVM-based models are applied to label the GO terms of miRNAs. The experimental results show that PmiRGO has a significantly better performance than existing state-of-the-art methods in terms of F-max. A case study further demonstrates the feasibility of PmiRGO to annotate the potential functions of miRNAs.
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