Abstract
DNA fragment assembly is a critical and essential early task in a genome project. This task leads to an NP-hard combinatorial optimization problem, and thus, efficient approximate algorithms are required to tackle large problem instances. The Problem Aware Local Search (PALS) is one of the most efficient heuristics for this problem in the literature. PALS gives fairly good solutions but the probability of premature convergence to local optima is significant. In this paper, we propose two modifications to the PALS heuristic in order to ameliorate its performance. The first modification enables the algorithm to improve the tentative solutions in a more appropriate and beneficial way. The second modification permits a significant reduction in the computational demands of the algorithm without significant accuracy loss. Computational experiments confirm that our proposals lead to a more efficient and robust assembler, improving both accuracy and efficiency.
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Alba E, Dorronsoro B (2009) Cellular genetic algorithms, vol 42, chap 15—Bioinformatics: The DNA fragment assembly problem. Springer, Berlin, pp 203–210
Alba E, Luque G (2007) A new local search algorithm for the DNA fragment assembly problem. In: Cotta C, van Hemert J (eds) Evolutionary computation in combinatorial optimization: EvoCOP’07, LNCS, vol 4446, Springer, Valencia, Spain, pp 1–12
Alba E, Luque G (2008) A hybrid genetic algorithm for the dna fragment assembly problem. In: Cotta C, van Hemert J (eds) Recent Advances in Evolutionary Computation for Combinatorial Optimization, Studies in Computational Intelligence, vol 153, Springer, pp 101–112
Burks C, Engle M, Forrest S, Parsons R, Soderlund C, Stolorz P (1994) Stochastic optimization tools for genomic sequence assembly. Automated DNA sequencing and analysis. Academic Press, London, pp 249–259
Chen T, Skiena SS (1997) Trie-based data structures for sequence assembly. In: Proceedings of the 8th annual symposium on combinatorial pattern matching. Springer, Berlin, pp 206–223
Dorronsoro B, Alba E, Luque G, Bouvry P (2008) A self-adaptive cellular memetic algorithm for the DNA fragment assembly problem. In: Proceedings of IEEE congress on evolutionary computation, pp 2651–2658
Engle ML, Burks C (1993) Artificially generated data sets for testing DNA sequence assembly algorithms. Genomics 16(1):286–288
Firoz JS, Rahman MS, Saha TK (2012) Bee algorithms for solving DNA fragment assembly problem with noisy and noiseless data. In: Proceedings of the 14th annual conference on genetic and evolutionary computation, ACM, New York, pp 201–208
Green P (1994) Phrap, http://www.phrap.org
Huang KW, Chen JL, Yang CS, Tsai CW (2015) A memetic particle swarm optimization algorithm for solving the DNA fragment assembly problem. Neural Comput Appl 26(3):495–506
Huang X, Madan A (1999) CAP3: a DNA sequence assembly program. Genome Res 9(9):868–877
Kubalik J, Buryan P, Wagner L (2010) Solving the DNA fragment assembly problem efficiently using iterative optimization with evolved hypermutations. In: Proceedings of the 12th annual conference on Genetic and evolutionary computation, ACM, New York, pp 213–214
Li L, Khuri S (2004) A comparison of DNA fragment assembly algorithms. METMBS 4:329–335
Luque G, Alba E, Khuri S (2006) Parallel Algorithms for bioinformatics. Assembling DNA fragments with a distributed genetic algorithm, chapter 16. Wiley, New York
Mallén-Fullerton GM, Hughes JA, Houghten S, Fernández-Anaya G (2013) Benchmark datasets for the DNA fragment assembly problem. Int J Bio-Inspired Comput 5(6):384–394
Meksangsouy P, Chaiyaratana N (2003) DNA fragment assembly using an ant colony system algorithm. In: Evolutionary computation, 2003. CEC’03. The 2003 Congress, IEEE, vol 3, pp 1756–1763
Minetti G, Alba E, Luque G (2008) Seeding strategies and recombination operators for solving the DNA fragment assembly problem. Inf Process Lett 108(3):94–100
Minetti G, Leguizamón G, Alba E (2014) An improved trajectory-based hybrid metaheuristic applied to the noisy DNA fragment assembly problem. Inf Sci 277:273–283
Myers EW (1995) Toward simplifying and accurately formulating fragment assembly. J Comput Biol 2(2):275–290
Nebro AJ, Luque G, Luna F, Alba E (2008) DNA fragment assembly using a grid-based genetic algorithm. Comput Op Res 35(9):2776–2790
Parsons RJ, Forrest S, Burks C (1995) Genetic algorithms, operators, and DNA fragment assembly. Mach Learn 21(1–2):11–33
Pevzner P (2000) Computational molecular biology: an algorithmic approach. MIT Press, Cambridge
Pop M (2004) Shotgun sequence assembly. Adv Comput 60:193–248
Setubal JC, Meidanis J (1997) Introduction to computational molecular biology. Fragment assembly of DNA, Chap 4. University of Campinas, Brazil, pp 105–139
Sutton GG, White O, Adams MD, Kerlavage AR (1995) TIGR assembler: a new tool for assembling large shotgun sequencing projects. Genome Sci Technol 1(1):9–19
Acknowledgments
The work of the first author was partially funded by grants from the Algerian Ministry of Higher Education and Scientific Research. The Spanish authors acknowledge funds by the project number 8.06/5.47.4142 in collaboration with the VSB-Technical University of Ostrava, the Spanish Ministry of Sciences and Innovation European FEDER under contract TIN2014-57341-R (moveON project), and UMA/FEDER FC14-TIC36, Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech.
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Ben Ali, A., Luque, G., Alba, E. et al. An improved problem aware local search algorithm for the DNA fragment assembly problem. Soft Comput 21, 1709–1720 (2017). https://doi.org/10.1007/s00500-015-1875-2
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DOI: https://doi.org/10.1007/s00500-015-1875-2