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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2021
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| 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 |