A metaheuristic approach for the sequencing by hybridization problem with positive and negative errors

Authors:
Athanassios Nikolakopoulos;Haralambos Sarimveis
Affiliations:
School of Chemical Engineering, National Technical University of Athens, 9 Heroon Polytechniou str. Zografou Campus, 15780 Athens, Greece;School of Chemical Engineering, National Technical University of Athens, 9 Heroon Polytechniou str. Zografou Campus, 15780 Athens, Greece
Venue:
Engineering Applications of Artificial Intelligence
Year:
2008

Citing 5
Cited 3

Threshold accepting: a general purpose optimization algorithm appearing superior to simulated annealing

Journal of Computational Physics
Hybrid Genetic Algorithm for DNA Sequencing with Errors

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Complexity of DNA sequencing by hybridization

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Probabilistic nucleotide assembling method for sequencing by hybridization

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Tabu search algorithm for DNA sequencing by hybridization with isothermic libraries

Computational Biology and Chemistry

A math-heuristic algorithm for the DNA sequencing problem

LION'10 Proceedings of the 4th international conference on Learning and intelligent optimization
An integer programming approach to DNA sequence assembly

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A hybrid algorithm for the DNA sequencing problem

Discrete Applied Mathematics

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Abstract

This work introduces a metaheuristic method for the reconstruction of the DNA string from its l-mer content in the presence of large amounts of positive and negative errors. The procedure consists of three parts: the formulation of the problem as an asymmetric traveling salesman problem (ATSP), a technique for handling the positive errors and an optimization algorithm that solves the formulated problem. The optimization algorithm is a variation of the threshold accepting method with intense local search and its function is controlled by a size diminishing shell. The optimization algorithm is used consecutively on ATSPs of continuously decreasing sizes till it reaches a final solution. The proposed method provides solutions of better quality compared to algorithms in the recent bibliography.