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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...
| Autores principales: | , , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2009
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| Materias: | |
| 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 |