SGAEMDA: Predicting miRNA-Disease Associations Based on Stacked Graph Autoencoder

MicroRNA (miRNA)-disease association (MDA) prediction is critical for disease prevention, diagnosis, and treatment. Traditional MDA wet experiments, on the other hand, are inefficient and costly.Therefore, we proposed a multi-layer collaborative unsupervised training base model called SGAEMDA (Stack...

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Detalles Bibliográficos
Autores principales: Wang, Shudong, Lin, Boyang, Zhang, Yuanyuan, Qiao, Sibo, Wang, Fuyu, Wu, Wenhao, Ren, Chuanru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9776508/
https://www.ncbi.nlm.nih.gov/pubmed/36552748
http://dx.doi.org/10.3390/cells11243984

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9776508/
https://www.ncbi.nlm.nih.gov/pubmed/36552748
http://dx.doi.org/10.3390/cells11243984

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