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A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations

BACKGROUND: Numerous studies have demonstrated that long non-coding RNAs are related to plenty of human diseases. Therefore, it is crucial to predict potential lncRNA-disease associations for disease prognosis, diagnosis and therapy. Dozens of machine learning and deep learning algorithms have been...

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Detalles Bibliográficos
Autores principales: Shi, Zhuangwei, Zhang, Han, Jin, Chen, Quan, Xiongwen, Yin, Yanbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7983260/
https://www.ncbi.nlm.nih.gov/pubmed/33745450
http://dx.doi.org/10.1186/s12859-021-04073-z