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 interaction...

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Detalles Bibliográficos
Autores principales: Li, Chunyan, Liu, Hongju, Hu, Qian, Que, Jinlong, Yao, Junfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6769654/
https://www.ncbi.nlm.nih.gov/pubmed/31455028
http://dx.doi.org/10.3390/cells8090977

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6769654/
https://www.ncbi.nlm.nih.gov/pubmed/31455028
http://dx.doi.org/10.3390/cells8090977

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