Abstract
This paper presents a genetic algorithm for an important computational biology problem. The problem appears in the computational part of a new proposal for DNA sequencing denominated sequencing by hybridization. The general usage of this method for real sequencing purposes depends mainly on the development of good algorithmic procedures for solving its computational phase. The proposed genetic algorithm is a modified version of a previously proposed hybrid genetic algorithm for the same problem. It is compared with two well suited meta-heuristic approaches reported in the literature: the hybrid genetic algorithm, which is the origin of our proposed variant, and a tabu-scatter search algorithm. Experimental results carried out on real DNA data show the advantages of using the proposed algorithm. Furthermore, statistical tests confirm the superiority of the proposed variant over the state-of-the-art heuristics.
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Brizuela, C.A., González-Gurrola, L.C., Tchernykh, A. et al. Sequencing by hybridization: an enhanced crossover operator for a hybrid genetic algorithm. J Heuristics 13, 209–225 (2007). https://doi.org/10.1007/s10732-007-9014-6
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DOI: https://doi.org/10.1007/s10732-007-9014-6