Variational graph auto-encoders for miRNA-disease association prediction

•Variational graph auto-encoders are excellent for predicting miRNA-disease associations.•Graph convolutional networks obtain good representations for miRNAs and diseases.•Variational auto-encoders can deal with missing data in the miRNA-disease network.•Integrating different databases helps predict...

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Bibliographic Details
Published in:	Methods (San Diego, Calif.) Vol. 192; pp. 25 - 34
Main Authors:	Ding, Yulian, Tian, Li-Ping, Lei, Xiujuan, Liao, Bo, Wu, Fang-Xiang
Format:	Journal Article
Language:	English
Published:	United States Elsevier Inc 01.08.2021
Subjects:	Algorithms case studies Computational Biology Deep learning Graph convolutional network human diseases Humans microRNA MicroRNAs - genetics miRNA-disease association Neural Networks, Computer prediction Variational autoencoder Deep learning Variational autoencoder Graph convolutional network miRNA-disease association
ISSN:	1046-2023, 1095-9130, 1095-9130
Online Access:	Get full text
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