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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 9, 2021.
Abstract: ZIKV is a mosquito-borne disease. It is known to cause neurological disorders and congenital disabilities in newborns. The Genome Sequence of the Zika virus is used for the study. The essential cell functionalities like circadian behavior and expression of genes are studied. Regulatory proteins are alternating functionalities during daytime and night time. Identifying motif is made by understanding the features of motifs, finding the count matrix, and formulating the profile matrix. The consensus string of the Zika virus is to be computed, and the score motif is to be calculated. Different techniques of motif finding like the Brute Force technique and Greedy Search techniques are proposed. In the Brute Force technique, each motif is selected, its score is to be calculated, and then the minimum score can be obtained. The Brute Force technique will take an enormous amount of time, but it is guaranteed to find a solution. The Greedy Search technique is not guaranteed to find motif like the Brute Force technique but can give a close answer in a realistic time. This paper presents the identification of motif in the Zika virus genome using programming techniques.
Pushpa Susant Mahapatro and Jatinderkumar R. Saini, “Genetic Behaviour of Zika Virus and Identification of Motif” International Journal of Advanced Computer Science and Applications(IJACSA), 12(9), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120967
@article{Mahapatro2021,
title = {Genetic Behaviour of Zika Virus and Identification of Motif},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120967},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120967},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {9},
author = {Pushpa Susant Mahapatro and Jatinderkumar R. Saini}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.