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 focus...

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Bibliographic Details
Published in:BMC bioinformatics Vol. 10; no. 1; p. 260
Main Authors: Kim, Eun-Youn, Kim, Seon-Young, Ashlock, Daniel, Nam, Dougu
Format: Journal Article
Language:English
Published: London BioMed Central 22.08.2009
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
ISSN:1471-2105, 1471-2105
Online Access:Get full text
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