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Iterated Local Search for de Novo Genomic Sequencing

  • Bernabé Dorronsoro
  • Pascal Bouvry
  • Enrique Alba
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6114)

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.

Keywords

Perturbation Method Small Instance Iterate Local Search Large Problem Instance Swap Operation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Bernabé Dorronsoro
    • 1
  • Pascal Bouvry
    • 1
  • Enrique Alba
    • 2
  1. 1.University of LuxembourgLuxembourg
  2. 2.University of MálagaSpain

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