Genetic Algorithm for Double Digest Problem

  • S. Sur-Kolay
  • S. Banerjee
  • S. Mukhopadhyaya
  • C. A. Murthy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3776)


The strongly NP-complete Double Digest Problem (DDP) for physical mapping of DNA, is now used for efficient genotyping. An instance of DDP has multiple distinct solutions. Existing methods produce a single solution, and are slow for large instances. We employ a type of equivalence among the distinct solutions to obtain almost all of them. Our method comprises of first finding a solution from each equivalence class by an elitist genetic algorithm, and then generating entire classes. Notable efficiency was achieved due to significant reduction in search space.


Genetic Algorithm Search Space Equivalence Class Valid Solution Distinct Solution 
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.


  1. 1.
    Bhandari, D., Murthy, C.A., Pal, S.K.: Genetic algorithm with elitist model and its convergence. International Journal of Pattern Recognition and Artificial Intelligence 10, 1147–1151 (1999)Google Scholar
  2. 2.
    Cieliebak, M., Eidenbenz, S., Woeginger, G.J.: Double digest revisited: Complexity and approximability in the presence of noisy data. Technical Report No. 382, ETH Zurich, Department of Computer Science (2002)Google Scholar
  3. 3.
    Cedeno, W., Vemuri, V., Rao and Slezak, T.: Multi-niche crowding in genetic algorithms and its application to the assembly of DNA Restriction-fragments. Evolutionary Computation 2(4), 321–345 (1994)CrossRefGoogle Scholar
  4. 4.
    Goldberg, D.E.: Genetic Algorithm in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)Google Scholar
  5. 5.
    Goldstein, L., Waterman, M.S.: Mapping DNA by stochastic relaxation. Advances in Applied Mathematics 8, 194–207 (1987)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Inglehart, J., Nelson, P.C.: On the limitations of automated restriction mapping. Computer Applications in the Biosciences (CABIOS) 10(3), 249–261 (1994)Google Scholar
  7. 7.
    Kao, M.-Y., Samet, J., Sung, W.-K.: The enhanced double digest problem for DNA physical mapping. In: Halldórsson, M.M. (ed.) SWAT 2000. LNCS, vol. 1851, pp. 383–392. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  8. 8.
    Nathans, D., Smith, H.O.: Restriction endonucleases in the analysis and restructuring of DNA molecules. Annual Review of Biochemistry 44, 273–293 (1975)CrossRefGoogle Scholar
  9. 9.
    Pevzner, P.A.: Computational Molecular Biology: An Algorithmic Approach. MIT Press, Cambridge (2000)zbMATHGoogle Scholar
  10. 10.
    Schmitt, W., Waterman, M.S.: Multiple solutions of DNA restriction mapping problem. Advances in Applied Mathematics 12, 412–427 (1991)zbMATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    Smith, H.O., Wilcox, K.W.: A restriction enzyme from Hemophilus influenzae. I. Purification and general properties. Journal of Molecular Biology 147, 379–391 (1970)CrossRefGoogle Scholar
  12. 12.
    Waterman, M.S.: Introduction to Computational Biology: Maps, sequences and genomes. Chapman and Hall, UK (1995)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • S. Sur-Kolay
    • 1
  • S. Banerjee
    • 2
  • S. Mukhopadhyaya
    • 1
  • C. A. Murthy
    • 1
  1. 1.Indian Statistical InstituteKolkataIndia
  2. 2.Honeywell Technology Solutions Lab Pvt. Ltd.BangaloreIndia

Personalised recommendations