Rough Based Clustering For Gene Expression Data –A Survey - Udhaya Bharathy, C; Rathika, C (International Journal of Computer Sciences and Engineering, 2025)
Microarray technology has made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. But the high dimensionality property of gene expression data makes it difficult to be analyzed. Clustering associated with the concept of rough set theory is very effective in such situations. This paper gives a briefly introduction about the concepts of RST, clustering, gene expression, microarray technology and discuss the basic elements of clustering on gene expression data. It also explain why rough clustering is preferred over other conventional methods by presenting a survey on few clustering algorithms based on rough set theory for gene expression data. Finally it concludes by stating that this area proves to be potential research field for the research community.