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MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering

BACKGROUND: Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focu...

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Detalhes bibliográficos
Main Authors: Kim, Eun-Youn, Kim, Seon-Young, Ashlock, Daniel, Nam, Dougu
Formato: Artigo
Idioma:Inglês
Publicado em: BioMed Central 2009
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC2743671/
https://ncbi.nlm.nih.gov/pubmed/19698124
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-10-260
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