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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 4, 2020.
Abstract: The comparison of genomic sequences plays a key role in determining the structural and functional relationships between genes. This comparison is carried out by identifying the similarities, differences and mutations between genomic sequences. This makes it possible to study and analyze the genetic and the evolutionary relationships between organisms. Alignment algorithms have been in the spotlight for the last few decades, due to a vast genomic data explosion. They have attracted a great deal of interest from many researchers who focus on the development of practical solutions to ensure effective alignments with an optimal response time. In this paper, a novel algorithm based on Discrete To Continuous "DTC" approach has been developed. The proposed methodology was compared against other existing methods, which are largely based on the concept of string matching. Experimental results show that the DTC algorithm delivers supremely efficient alignment with a reduced response time.
Wajih Rhalem, Jamal El Mhamdi, Mourad Raji, Ahmed Hammouch, Aqili Nabil, Nassim Kharmoum and Hassan Ghazal, “An Efficient and Rapid Method for Detection of Mutations in Deoxyribonucleic Acid - Sequences” International Journal of Advanced Computer Science and Applications(IJACSA), 11(4), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110438
@article{Rhalem2020,
title = {An Efficient and Rapid Method for Detection of Mutations in Deoxyribonucleic Acid - Sequences},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110438},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110438},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {4},
author = {Wajih Rhalem and Jamal El Mhamdi and Mourad Raji and Ahmed Hammouch and Aqili Nabil and Nassim Kharmoum and Hassan Ghazal}
}
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.