Detection of Longest Common Sub Sequence in Normal DNA and Dengue Virus Affected Human DNA using Self Organizing Map - Tamilpavai, G; Vishnuppriya, C (International Journal of Computer Sciences and Engineering, 2020)
Bioinformatics is an active research area which combines biological matter as well as computer science research. Detection of disease causing human Deoxyribo Nucleic Acid (DNA) sequence analysis is one of the major application areas under bioinformatics. Among the severe diseases, the number of Dengue cases and deaths are raised in Tamil Nadu. Identification of sequence motifs involved in Dengue virus is essential for early prediction and saving human life. It includes wide ranges of steps for disease diagnosing. The scope of this proposed work is to provide the longest common subsequence which present in a normal and Dengue virus affected human DNA sequence. The human DNA sequences are collected from National Center for Biotechnology Information (NCBI) database. Human DNA sequence is separated as k-mer using k-mer separation rule. From that, the separated k-mers are clustered using Self Organizing Map (SOM) algorithm. In which mean, median and standard deviation are used as features for clustering k-mers. Then obtained k-mers clusters are given to the Longest Common Subsequence (LCSS) algorithm to find common subsequence with higher length, which presents in every kmers clusters. Time consumption for identification of LCSS is compared for both normal and Dengue virus affected DNA.