MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering |
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| Authors: | Eun-Youn Kim Seon-Young Kim Daniel Ashlock and Dougu Nam |
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| Institution: | (1) National Institute for Mathematical Sciences (NIMS), Yuseong, Daejeon, 305–340, Republic of Korea;(2) Korea Research Institute of Bioscience and Biotechnology (KRIBB), PO Box 115, Yuseong, Daejeon, 305–600, Republic of Korea;(3) Department of Mathematics and Statistics, University of Guelph, Ontario, N1G 2R4, Canada |
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| Abstract: | 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 on clusters with compact shapes and do not reflect the geometric complexity of the high
dimensional microarray clusters, which limits their performance. |
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