Predicting MiRNA-disease associations by multiple meta-paths fusion graph embedding model

BACKGROUND: Many studies prove that miRNAs have significant roles in diagnosing and treating complex human diseases. However, conventional biological experiments are too costly and time-consuming to identify unconfirmed miRNA-disease associations. Thus, computational models predicting unidentified m...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Lei, Liu, Bailong, Li, Zhengwei, Zhu, Xiaoyan, Liang, Zhizhen, An, Jiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7579830/
https://www.ncbi.nlm.nih.gov/pubmed/33087064
http://dx.doi.org/10.1186/s12859-020-03765-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7579830/
https://www.ncbi.nlm.nih.gov/pubmed/33087064
http://dx.doi.org/10.1186/s12859-020-03765-2

Ejemplares similares