Clustering microarray data using fuzzy clustering with viewpoints

Abstract

This paper studies the application of fuzzy clustering with viewpoints in order to cluster cell samples according to their gene expression profile. This method combines fuzzy clustering with external domain knowledge represented by the so-called viewpoints. The viewpoints that we employ are obtained from previously available expression data. The method was compared to the clustering algorithms of k-means, fuzzy c-means, affinity propagation, as well as a method of clustering microarray data that is based on prior biological knowledge, and has shown comparable/improved results over them.