RCMF: a robust collaborative matrix factorization method to predict miRNA-disease associations

BACKGROUND: Predicting miRNA-disease associations (MDAs) is time-consuming and expensive. It is imminent to improve the accuracy of prediction results. So it is crucial to develop a novel computing technology to predict new MDAs. Although some existing methods can effectively predict novel MDAs, the...

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Detalles Bibliográficos
Autores principales: Cui, Zhen, Liu, Jin-Xing, Gao, Ying-Lian, Zheng, Chun-Hou, Wang, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929455/
https://www.ncbi.nlm.nih.gov/pubmed/31874608
http://dx.doi.org/10.1186/s12859-019-3260-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929455/
https://www.ncbi.nlm.nih.gov/pubmed/31874608
http://dx.doi.org/10.1186/s12859-019-3260-0

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