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Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints
BACKGROUND: Identifying different types of cancer based on gene expression data has become hotspot in bioinformatics research. Clustering cancer gene expression data from multiple cancers to their own class is a significance solution. However, the characteristics of high-dimensional and small sample...
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| Publicado no: | BMC Bioinformatics |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6936083/ https://ncbi.nlm.nih.gov/pubmed/31888442 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-019-3231-5 |
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