http://www.iaeme.com/IJCIET/index.asp 17 editor@iaeme.com International Journal of Computer Engineering & Technology (IJCET) Volume 6, Issue 10, Oct 2015, pp. 17-33, Article ID: IJCET_06_10_003 Available online at http://www.iaeme.com/IJCET/issues.asp?JType=IJCET&VType=6&IType=10 ISSN Print: 0976-6367 and ISSN Online: 0976–6375 © IAEME Publication ___________________________________________________________________________ A NOVEL BIO-COMPUTATIONAL MODEL FOR MINING THE DENGUE GENE SEQUENCES T. Marimuthu 1 Research Scholar, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India V. Balamurugan Department of Information Technology, AMET University, Chennai, Tamilnadu, India ABSTRACT The evolution of dengue viruses has a major impact on the causes of dengue disease around the world. The analysis and interpretation of relationship among the dengue viruses have become a tedious problem due to the lack of computational models. Although, the biological models available like phylogenetic analysis which reveals the association between the dengue viruses, the computational techniques are required for further analysis such as to find the classification of new evolutionary virus type, DNA and RNA variation, protein structure prediction, protein-protein interaction. In this paper, we propose a bio- computational model called ‘Sequence Miner’ to interpret the relationship among the dengue viruses. In addition to that, the proposed model performs the classification among the given set of gene sequences based on novel periodic association rules and visualizing the results through the interactive tool. If the structure of a protein is known, it would be easier for the biologist to infer the function of the protein. However, it is still costly to decide the structure of a protein via biological models. On the contrary, protein sequences are relatively easy to obtain. Therefore, it is desirable that a protein’s structure can be decided from its sequence through computational models. The accuracy of the proposed model is 96.74 % which is calculated by giving the 10,735 varying length of the sequences as the input, 10, 198 sequences are correctly classified. Key words: DNA, RNA, Protein, classification, periodic association rules, phylogenetic tree and dengue virus. Cite this Article: Marimuthu, T. and Balamurugan, V. A Novel Bio- Computational Model for Mining the Dengue Gene Sequences. International Journal of Computer Engineering and Technology, 6(10), 2015, pp. 17-33. http://www.iaeme.com/IJCET/issues.asp?JType=IJCET&VType=6&IType=10