%0 Journal Article
	%A Seo Young Kim and  Tai Myong Choi
	%D 2007
	%J International Journal of Mathematical and Computational Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 4, 2007
	%T Fuzzy Types Clustering for Microarray Data 
	%U https://publications.waset.org/pdf/4776
	%V 4
	%X The main goal of microarray experiments is to quantify the expression of every object on a slide as precisely as possible, with a further goal of clustering the objects. Recently, many studies have discussed clustering issues involving similar patterns of gene expression. This paper presents an application of fuzzy-type methods for clustering DNA microarray data that can be applied to typical comparisons. Clustering and analyses were performed on microarray and simulated data. The results show that fuzzy-possibility c-means clustering substantially improves the findings obtained by others. 
	%P 229 - 232