This paper presents genetic algorithm based solution for determing alignment of multiple molecular sequences. Two datasets from DNA families Canis_familiaris and galaxy dataset have been considered for experimental work & analysis. Genetic operators like cross over rate, mutation rate can be defined by the user. Experiments & observations were recorded w.r.t variable parameters like fixed population size vs variable number of generations & vice versa, variable crossover & mutation rates. Comparative evaluation in terms of measure of fitness accuracy is also carried out w.r.t existing MSA tools like Maft, Kalign. Experimental results show that the proposed solution does offer better fitness accuracy rates.
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Genetic Algorithm Based Approach for Obtaining Alignment of Multiple Sequences
Semantic Scholar · Biology · 2012
Abstract
This paper presents genetic algorithm based solution for determing alignment of multiple molecular sequences. Two datasets from DNA families Canis_familiaris and galaxy dataset have been considered for experimental work & analysis. Genetic operators like cross over rate, mutation rate can be defined by the user. Experiments & observations were recorded w.r.t variable parameters like fixed population size vs variable number of generations & vice versa, variable crossover & mutation rates. Comparative evaluation in terms of measure of fitness accuracy is also carried out w.r.t existing MSA tools like Maft, Kalign. Experimental results show that the proposed solution does offer better fitness accuracy rates.
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