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Robust hypergraph regularized non-negative matrix factorization for sample clustering and feature selection in multi-view gene expression data
BACKGROUND: As one of the most popular data representation methods, non-negative matrix decomposition (NMF) has been widely concerned in the tasks of clustering and feature selection. However, most of the previously proposed NMF-based methods do not adequately explore the hidden geometrical structur...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805321/ https://www.ncbi.nlm.nih.gov/pubmed/31639067 http://dx.doi.org/10.1186/s40246-019-0222-6 |