Using an Adaptive Memory Strategy to Improve a Multistart Heuristic for Sequencing by Hybridization

  • Eraldo R. Fernandes
  • Celso C. Ribeiro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3503)


We describe a multistart heuristic using an adaptive memory strategy for the problem of sequencing by hybridization. The memory-based strategy is able to significantly improve the performance of memoryless construction procedures, in terms of solution quality and processing time. Computational results show that the new heuristic obtains systematically better solutions than more involving and time consuming techniques such as tabu search and genetic algorithms.


Genetic Algorithm Target Sequence Tabu Search Test Instance Average Similarity 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aiex, R.M., Resende, M.G.C., Ribeiro, C.C.: Probability distribution of solution time in GRASP: An experimental investigation. Journal of Heuristics 8, 343–373 (2002)zbMATHCrossRefGoogle Scholar
  2. 2.
    Benson, D.A., Karsch-Mizrachi, I., Lipman, D.J., Ostell, J., Wheeler, D.L.: Genbank: Update. Nucleic Acids Research 32, D23–D26 (2004)Google Scholar
  3. 3.
    Blazewicz, J., Formanowicz, P., Guinand, F., Kasprzak, M.: A heuristic managing errors for DNA sequencing. Bioinformatics 18, 652–660 (2002)CrossRefGoogle Scholar
  4. 4.
    Blazewicz, J., Formanowicz, P., Kasprzak, M., Markiewicz, W.T., Weglarz, T.: Tabu search for DNA sequencing with false negatives and false positives. European Journal of Operational Research 125, 257–265 (2000)zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Blazewicz, J., Kasprzak, M.: Complexity of DNA sequencing by hybridization. Theoretical Computer Science 290, 1459–1473 (2003)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Endo, T.A.: Probabilistic nucleotide assembling method for sequencing by hybridization. Bioinformatics 20, 2181–2188 (2004)CrossRefGoogle Scholar
  7. 7.
    Fleurent, C., Glover, F.: Improved constructive multistart strategies for the quadratic assignment problem using adaptive memory. INFORMS Journal on Computing 11, 198–204 (1999)zbMATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Pevzner, P.A.: Computational molecular biology: An algorithmic approach. MIT Press, Cambridge (2000)zbMATHGoogle Scholar
  9. 9.
    Waterman, M.S.: Introduction to computational biology: Maps, sequences and genomes. Chapman & Hall, Boca Raton (1995)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Eraldo R. Fernandes
    • 1
  • Celso C. Ribeiro
    • 2
  1. 1.Department of Computer ScienceCatholic University of Rio de JaneiroRio de JaneiroBrazil
  2. 2.Department of Computer ScienceUniversidade Federal FluminenseNiteróiBrazil

Personalised recommendations