Fuzzy C-means method with empirical mode decomposition for clustering microarray data
by Yan-Fei Wang; Zu-Guo Yu; Vo Anh
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 7, No. 2, 2013

Abstract: Microarray techniques have revolutionised genomic research by making it possible to monitor the expression of thousands of genes in parallel. The Fuzzy C-Means (FCM) method is an efficient clustering approach devised for microarray data analysis. However, microarray data contains noise, which would affect clustering results. In this paper, we propose to combine the FCM method with the Empirical Mode Decomposition (EMD) for clustering microarray data to reduce the effect of the noise. The results suggest the clustering structures of denoised microarray data are more reasonable and genes have tighter association with their clusters than those using FCM only.

Online publication date: Mon, 20-Oct-2014

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