Abstract

ITS2, a well known phylogenetic marker is widely used in taxonomic studies. This study exploits a novel approach to classify and cluster the Anopheline species based upon their spacer (ITS2) sequences. As secondary structure of ITS2 is crucial for the function, derived parameters based on secondary structure along with sequence composition were considered for this study. Self Organizing Map (SOM), a neural network approach was adopted for classification and clustering of Anopheline sequences. This data mining approach for clustering and classification will aid in unveiling of inherent relationships among the various parameters contributing to ITS2 structure stability.

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