Abstract
The sequencing process of a DNA chain for reading its components supposes a complex process, since only small DNA fragments can be read nowadays. Therefore, the use of optimization algorithms is required to rebuild a single chain from all the small pieces. We address here a simplified version of the problem, in which no errors in the sequencing process are allowed. The methods typically used in the literature for this problem are not satisfactory when solving realistic size instances, so there is a need for new more efficient and accurate methods. We propose a new iterated local search algorithm, highly competitive with the best algorithms in the literature, and considerably faster.
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Dorronsoro, B., Bouvry, P., Alba, E. (2010). Iterated Local Search for de Novo Genomic Sequencing. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artifical Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13232-2_52
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DOI: https://doi.org/10.1007/978-3-642-13232-2_52
Publisher Name: Springer, Berlin, Heidelberg
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