A Novel Computational Model for Predicting microRNA–Disease Associations Based on Heterogeneous Graph Convolutional Networks

A Novel Computational Model for Predicting microRNA–Disease Associations Based on Heterogeneous Graph Convolutional Networks

Identifying the interactions between disease and microRNA (miRNA) can accelerate drugs development, individualized diagnosis, and treatment for various human diseases. However, experimental methods are time-consuming and costly. So computational approaches to predict latent miRNA−disease i...

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Bibliographic Details
Main Authors: Chunyan Li, Hongju Liu, Qian Hu, Jinlong Que, Junfeng Yao
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Cells
Subjects:
disease
microRNA
heterogeneous
graph
convolution network
negative sampling
cross validation
Online Access:https://www.mdpi.com/2073-4409/8/9/977

Internet

https://www.mdpi.com/2073-4409/8/9/977

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