%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