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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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Autors principals: Kim, Eun-Youn, Kim, Seon-Young, Ashlock, Daniel, Nam, Dougu
Format: Artigo
Idioma:Inglês
Publicat: BioMed Central 2009
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Accés en línia: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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