On Clustering of DNA Sequence of Olfactory Receptors Using Scaled Fuzzy Graph Model

Abstract

Olfactory perception is the sense of smell that allows an organism to detect chemical in its environment. The first step in odor transduction is mediated by binding odorants to olfactory receptors (ORs) which belong to the heptahelical G-protein-coupled receptor (GPCR) super-family. Mammalian ORs are disposed in clusters on virtually all chromosomes. They are encoded by the largest multigene family ($\sim$1000 members) in the genome of mammals and Caenorhabditis elegans, whereas Drosophila contains only 60 genes. Each OR specifically recognizes a set of odorous molecules that share common molecular features. However, local mutations affect the DNA sequences of these receptors. Hence, to study the changes among affected and non-affected, we use unsupervised learning (clustering). In this paper, a scaled fuzzy graph model for clustering has been used to study the changes before and after the local mutation on DNA sequences of ORs. At the fractional dimensional level, our experimental study confirms its accuracy.