Abstract
Olfactory receptors (ORs) are responsible for recognition of odor molecules. The deoxyribonucleic acid (DNA) sequences of these receptors are severely affected by local mutations. Therefore, to study the changes among affected and non-affected ORs, the authors attempted to use unsupervised learning (clustering) algorithm. In this paper, they have used a scaled fuzzy graph model for clustering to study the changes before and after the local mutation on DNA sequences of ORs. Their simulation study at the fractional dimensional level confirms its accuracy.
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