SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost

BACKGROUND: Identifying miRNA and disease associations helps us understand disease mechanisms of action from the molecular level. However, it is usually blind, time-consuming, and small-scale based on biological experiments. Hence, developing computational methods to predict unknown miRNA and diseas...

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Detalles Bibliográficos
Autores principales: Liu, Dayun, Huang, Yibiao, Nie, Wenjuan, Zhang, Jiaxuan, Deng, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082881/
https://www.ncbi.nlm.nih.gov/pubmed/33910505
http://dx.doi.org/10.1186/s12859-021-04135-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082881/
https://www.ncbi.nlm.nih.gov/pubmed/33910505
http://dx.doi.org/10.1186/s12859-021-04135-2

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