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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Detalles Bibliográficos
Autores principales: Kim, Eun-Youn, Kim, Seon-Young, Ashlock, Daniel, Nam, Dougu
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2743671/
https://www.ncbi.nlm.nih.gov/pubmed/19698124
http://dx.doi.org/10.1186/1471-2105-10-260

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2743671/
https://www.ncbi.nlm.nih.gov/pubmed/19698124
http://dx.doi.org/10.1186/1471-2105-10-260

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