CLUSTERING GENE EXPRESSION DATA WITH KERNEL PRINCIPAL COMPONENTS
Zhenqiu Liu, Dechang Chen, Halima Bensmail, Ying Xu · Journal of Bioinformatics and Computational Biology · 2005
Kernel principal component analysis (KPCA) has been applied to data clustering and graphic cut in the last couple of years. This paper discusses the application of KPCA to microarray data clustering. A new algorithm based on KPCA and fuzzy C-means is proposed. Experiments with microarray data show that the proposed algorithms is in general superior to traditional algorithms.