A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network

Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in ord...

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Detalles Bibliográficos
Autores principales: Zhang, Xiaotian, Yin, Jian, Zhang, Xu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5867860/
https://www.ncbi.nlm.nih.gov/pubmed/29498680
http://dx.doi.org/10.3390/genes9030139

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5867860/
https://www.ncbi.nlm.nih.gov/pubmed/29498680
http://dx.doi.org/10.3390/genes9030139

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