Cargando…
Improved Prediction of miRNA-Disease Associations Based on Matrix Completion with Network Regularization
The identification of potential microRNA (miRNA)-disease associations enables the elucidation of the pathogenesis of complex human diseases owing to the crucial role of miRNAs in various biologic processes and it yields insights into novel prognostic markers. In the consideration of the time and cos...
Autores principales: | Ha, Jihwan, Park, Chihyun, Park, Chanyoung, Park, Sanghyun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226829/ https://www.ncbi.nlm.nih.gov/pubmed/32260218 http://dx.doi.org/10.3390/cells9040881 |
Ejemplares similares
-
PMAMCA: prediction of microRNA-disease association utilizing a matrix completion approach
por: Ha, Jihwan, et al.
Publicado: (2019) -
MDMF: Predicting miRNA–Disease Association Based on Matrix Factorization with Disease Similarity Constraint
por: Ha, Jihwan
Publicado: (2022) -
MCMDA: Matrix completion for MiRNA-disease association prediction
por: Li, Jian-Qiang, et al.
Publicado: (2017) -
Heterogeneous Graph Convolutional Networks and Matrix Completion for miRNA-Disease Association Prediction
por: Zhu, Rongxiang, et al.
Publicado: (2020) -
SNFIMCMDA: Similarity Network Fusion and Inductive Matrix Completion for miRNA–Disease Association Prediction
por: Li, Lei, et al.
Publicado: (2021)