DocumentCode :
3101205
Title :
Multiple sequence alignment using genetic algorithm and simulated annealing
Author :
Omar, Mohd Faizal ; Salam, Rosalina Abdul ; Rashid, Nur´Aini Abdul ; Abdullah, Rosni
Author_Institution :
Sch. of Comput. Sci., Univ. Sains Malaysia, Penang, Malaysia
fYear :
2004
fDate :
19-23 April 2004
Firstpage :
455
Lastpage :
456
Abstract :
This paper presents the combination of genetic algorithm and simulated annealing to solve multiple sequence alignment (MSA) assignment. Genetic algorithm will try to find a new region of feasible solution while simulated annealing will act as an aligning improver. There are several aspects that must be taken into consideration such as the representation, evaluation function and operator. Simulated annealing also helps to prevent local minima problem. Sequence similarity plays a major role in Bioinformatics and molecular biology. Significant results were produced from the prealignment and genetic algorithm phase.
Keywords :
biology computing; genetic algorithms; molecular biophysics; simulated annealing; bioinformatics; genetic algorithm; local minima problem; molecular biology; multiple sequence alignment; prealignment phase; simulated annealing; Biological system modeling; Computational modeling; Computer science; Genetic algorithms; Hidden Markov models; Iterative algorithms; Proteins; Sequences; Simulated annealing; Writing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technologies: From Theory to Applications, 2004. Proceedings. 2004 International Conference on
Print_ISBN :
0-7803-8482-2
Type :
conf
DOI :
10.1109/ICTTA.2004.1307828
Filename :
1307828
Link To Document :
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