FLBC: A Fuzzy Link based Clustering approach for gene expression data

In this paper, we propose an algorithm for efficient clustering of gene expression data. The algorithm uses the concept of common neighbors and uses a fuzzy approach for detecting intersecting and overlapping clusters. We have also compared the algorithm to the existing popular approaches and found our algorithm to give good results in terms of z-score measure of cluster validity and p-value measure.