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Semi-supervised consensus clustering for gene expression data analysis
BACKGROUND: Simple clustering methods such as hierarchical clustering and k-means are widely used for gene expression data analysis; but they are unable to deal with noise and high dimensionality associated with the microarray gene expression data. Consensus clustering appears to improve the robustn...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2014
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4036113/ https://www.ncbi.nlm.nih.gov/pubmed/24920961 http://dx.doi.org/10.1186/1756-0381-7-7 |