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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...
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| Autors principals: | , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
BioMed Central
2014
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4036113/ https://ncbi.nlm.nih.gov/pubmed/24920961 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1756-0381-7-7 |
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