MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering.
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BMC bioinformatics, ISSN: 1471-2105, Vol: 10, Issue: 1, Page: 260
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- Biochemistry, Genetics and Molecular Biology; Computer Science; Mathematics; Ensemble clustering; Geometric complexity; High-dimensional structures; K-means clustering; Microarray clusters; Original algorithms; Sample classification; Unsupervised clustering methods
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 on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance.