Clustering Microarray Data with Space Filling Curves

Authors:
Dimitrios Vogiatzis;Nicolas Tsapatsoulis
Affiliations:
Department of Computer Science, University of Cyprus, CY 1678, Cyprus, Phone: +357-2289-2749, Fax: +357-2289-2701,;Department of Telecommunications Science and Technology University of, Peloponnese, Greece
Venue:
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Year:
2007

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Abstract

We introduce a new clustering method for DNA microarray data that is based on space filling curves and wavelet denoising. The proposed method is much faster than the established fuzzy c-means clustering because clustering occurs in one dimension and it clusters cells that contain data, instead of data themselves. Moreover, preliminary evaluation results on data sets from Small Round Blue-Cell tumors, Leukemia and Lung cancer microarray experiments show that it can be equally or more accurate than fuzzy c-means clustering or a gaussian mixture model.