In the current paper, we have developed two bio-inspired fuzzy clustering algorithms by
incorporating the optimization techniques, namely differential evolution and particle swarm …

In this paper a fuzzy point symmetry based genetic clustering technique (Fuzzy-VGAPS) is
proposed which can automatically determine the number of clusters present in a data set as …

The invention of micro-array technology helps to keep the records containing expression
values of multiple genes over different experimental conditions. Clustering is an …

Recent advancement in microarray technology permits monitoring of the expression levels
of a large set of genes across a number of time points simultaneously. For extracting …

Clustering has been an area of intensive research for several decades because of its
multifaceted applications in innumerable domains. Clustering can be either Boolean, where …

In the big data era, clustering is one of the most popular data mining method. Most clustering
algorithms have complications like automatic cluster number determination, poor clustering …

In recent year, the problem of clustering in microarray data has been gaining significant
attention. However most of the clustering methods attempt to find the group of genes where …

Clustering aims at representing large datasets by a fewer number of prototypes or clusters. It
brings simplicity in modeling data and thus plays a central role in the process of knowledge …

Data clustering is a popular approach for automatically finding classes, concepts, or groups
of patterns. Clustering aims at representing large datasets by a fewer number of prototypes …

In microarray data analysis, clustering is a method that groups thousands of genes by their
similarities of expression levels, helping to analyze gene expression profiles. This method …