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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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Detalles Bibliográficos
Autores principales:	Wang, Juan, Lu, Cong-Hai, Liu, Jin-Xing, Dai, Ling-Yun, Kong, Xiang-Zhen
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2019
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6936083/ https://www.ncbi.nlm.nih.gov/pubmed/31888442 http://dx.doi.org/10.1186/s12859-019-3231-5

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