RESEARCH ARTICLE


A Simple Genetic Algorithm for Optimizing Multiple Sequence Alignment on the Spread of the SARS Epidemic



Siti Amiroch1, *, M. Syaiful Pradana1, M. Isa Irawan2, Imam Mukhlash2
1 Department of Mathematics, Universitas Islam Darul ‘Ulum, Lamongan, Indonesia
2 Department of Mathematics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia


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© 2019 Amiroch et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this Author at the Department of Mathematics, Universitas Islam Darul ‘Ulum, Lamongan, East-Java, Indonesia; Tel: +62 81330543222; E-mails: siti.amiroch@unisda.ac.id, amirast_117@yahoo.com


Abstract

Background:

Multiple sequence alignment is a method of getting genomic relationships between 3 sequences or more. In multiple alignments, there are 3 mutation network analyses, namely topological network system, mutation region network and network system of mutation mode. In general, the three analyses show stable and unstable regions that map mutation regions. This area of ​​mutation is described further in a phylogenetic tree which simultaneously illustrates the path of the spread of an epidemic, the Severe Acute Respiratory Syndrome (SARS) epidemic. The process of spreading the SARS viruses, in this case, is described as the process of phylogenetic tree formation, and as a novelty of this research, multiple alignments in the process are analyzed in detail and then optimized with genetic algorithms.

Methods:

The data used to form the phylogenetic tree for the spread of the SARS epidemic are 14 DNA sequences which are then optimized by using genetic algorithms. The phylogenetic tree is constructed by using the neighbor-joining algorithm with a distance matrix that the intended distance is the genetic distance obtained from sequence alignment by using the Needleman Wunsch Algorithm.

Results & Conclusion:

The results of the analysis obtained 3649 stable areas and 19 unstable areas. The results of phylogenetic tree from the network system analysis indicated that the spread of the SARS epidemic extended from Guangzhou 16/12/02 to Zhongshan 27/12/02, then spread simultaneously to Guangzhou 18/02/03 and Guangzhou hospital. After that, the virus reached Metropole, Zhongshan, Hongkong, Singapore, Taiwan, Hong kong, and Hanoi which then continued to Guangzhou 01/01/03 and Toronto at once. The results of the mutation region network system demonstrate decomposition of orthogonal mutations in the 1st order arc.

Keywords: Genetic algorithm, Multiple sequence alignment, Needleman wunsch algorithm, Optimization, Phylogenetic Tree, SARS epidemic.