GENE ONTOLOGY SIMILARITY METRIC BASED ON DAG USING DIABETIC GENE

Bioinformatics and Data Mining provide exciting and challenging researches in several application areas especially in computer science. The association between gene and diseases are analyzed using data mining techniques. The objective of the paper is to study the various similarity metrics for analyzing the diabetic gene using data mining technique. This paper provides with an overview of different similarity metrics for gene clustering. A similarity metric is proposed to cluster diabetic gees based on DAG structure of gene ontology. The experimental verification is analyzed for evaluating the cluster with biological validation. The current OMIM dataset is used for the proposed work.