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Detection of Longest Common Sub Sequence in Normal DNA and Dengue Virus Affected Human DNA using Self Organizing Map

G. Tamilpavai1 , C. Vishnuppriya2

  1. Dept. of Computer Science and Engineering, Government College of Engineering, Tirunelveli, Tamil Nadu, India.
  2. Dept. of Computer Science and Engineering, Government College of Engineering, Tirunelveli, Tamil Nadu, India.

Section:Research Paper, Product Type: Journal Paper
Volume-8 , Issue-1 , Page no. 1-7, Jan-2020

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v8i1.17

Online published on Jan 31, 2020

Copyright © G. Tamilpavai, C. Vishnuppriya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: G. Tamilpavai, C. Vishnuppriya, “Detection of Longest Common Sub Sequence in Normal DNA and Dengue Virus Affected Human DNA using Self Organizing Map,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.1, pp.1-7, 2020.

MLA Style Citation: G. Tamilpavai, C. Vishnuppriya "Detection of Longest Common Sub Sequence in Normal DNA and Dengue Virus Affected Human DNA using Self Organizing Map." International Journal of Computer Sciences and Engineering 8.1 (2020): 1-7.

APA Style Citation: G. Tamilpavai, C. Vishnuppriya, (2020). Detection of Longest Common Sub Sequence in Normal DNA and Dengue Virus Affected Human DNA using Self Organizing Map. International Journal of Computer Sciences and Engineering, 8(1), 1-7.

BibTex Style Citation:
@article{Tamilpavai_2020,
author = {G. Tamilpavai, C. Vishnuppriya},
title = {Detection of Longest Common Sub Sequence in Normal DNA and Dengue Virus Affected Human DNA using Self Organizing Map},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2020},
volume = {8},
Issue = {1},
month = {1},
year = {2020},
issn = {2347-2693},
pages = {1-7},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4987},
doi = {https://doi.org/10.26438/ijcse/v8i1.17}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i1.17}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4987
TI - Detection of Longest Common Sub Sequence in Normal DNA and Dengue Virus Affected Human DNA using Self Organizing Map
T2 - International Journal of Computer Sciences and Engineering
AU - G. Tamilpavai, C. Vishnuppriya
PY - 2020
DA - 2020/01/31
PB - IJCSE, Indore, INDIA
SP - 1-7
IS - 1
VL - 8
SN - 2347-2693
ER -

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Abstract

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 k-mers clusters. Time consumption for identification of LCSS is compared for both normal and Dengue virus affected DNA.

Key-Words / Index Term

Bioinformatics, K-mers, Longest Common Sub Sequence (LCSS), String pattern matching algorithms

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