The Minisatellite Transformation Problem Revisited: A Run Length Encoded Approach

  • Behshad Behzadi
  • Jean-Marc Steyaert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3240)


In this paper we present a more efficient algorithm for comparison of minisatellites which has complexity O(n3+ m3 + mn2+ nm2 +mn) where n and m are the lengths of the maps and n’ and m’ are the sizes of run-length encoded maps. We show that this algorithm makes a significant improvement for the real biological data, dividing the computing time by a factor 30 on a significant set of data.


Recurrence Relation Edit Distance Compact Representation Optimal Transformation Transformation Distance 
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.
    Apostolico, A., Landau, G.M., Skiena, S.: Matching for Run Length Encoded Strings. Journal of Complexity 15(1), 4–16 (1999)zbMATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Arbell, O., Landau, G.M., Mitchell, J.S.B.: Edit Distance of Run-Length Encoded Strings. Information Processing Letter 83(6), 307–314 (2002)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Bunke, H., Csirik, J.: An Improved Algorithm for Computing the Edit Distance of Run Length Coded Strings. Information Processing Letters 54, 93–96 (1995)zbMATHCrossRefGoogle Scholar
  4. 4.
    Behzadi, B., Steyaert, J.-M.: An Improved Algorithm for Generalized Comparison of Minisatellites. In: Baeza-Yates, R., Chávez, E., Crochemore, M. (eds.) CPM 2003. LNCS, vol. 2676, pp. 32–41. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  5. 5.
    Mäkinen, V., Navarro, G., Ukkonen, E.: Approximate Matching of Run-Length Compressed Strings. In: Amir, A., Landau, G.M. (eds.) CPM 2001. LNCS, vol. 2089, pp. 31–49. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  6. 6.
    Bérard, S., Rivals, E.: Comparison of Minisatellites. In: Proceedings of the 6th Annual International Conference on Research in Computational Molecular Biology, ACM Press, New York (2002)Google Scholar
  7. 7.
    Jobling, M.A., Bouzekri, N., Taylor, P.G.: Hypervariable digital DNA codes for human paternal lineages: MVR-PCR at the Y-specific minisatellite, MSY1(DYF155S1). Human Molecular Genetics 7(4), 643–653 (1998)CrossRefGoogle Scholar
  8. 8.
    Bouzekri, N., Taylor, P.G., Hammer, M.F., Jobling, M.A.: Novel mutation processes in the evolution of haploid minisatellites, MSY1: array homogenization without homogenization. Human Molecular Genetics 7(4), 655–659 (1998)CrossRefGoogle Scholar
  9. 9.
    Jeffreys, A.J., Tamaki, K., Macleod, A., Monckton, D.G., Neil, D.L., Armour, J.A.L.: Complex gene conversion events in germline mutation at human minisatellites. Nature Genetics 6, 136–145 (1994)CrossRefGoogle Scholar
  10. 10.
    Brión, M., Cao, R., Salas, A., Lareu, M.V., Carracedo, A.: New Method to Measure Minisatellite Variant Repeat Variation in Population Genetic Studies. American Journal of Human Biology 14, 421–428 (2002)CrossRefGoogle Scholar
  11. 11.
    Elemento, O., Gascuel, O., Lefranc, M.-P.: Reconstructing the duplication history of tandemly repeated genes. Molecular Biology and Evolution 19(3), 278–288 (2002)Google Scholar
  12. 12.
    Sankoff, D., Kruskal, J.B.: Time Warps, String Edits and Macromolecules: The Theory and Practice of Sequence Comparison. Addison-Wesley, Reading (1983)Google Scholar
  13. 13.
    Crochemore, M., Landau, G.M., Ziv-Ukelson, M.: A sub-quadratic sequence alignment algorithm for unrestricted cost matrices. In: SODA 2002, pp. 679–688. ACM-SIAM (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Behshad Behzadi
    • 1
  • Jean-Marc Steyaert
    • 1
  1. 1.LIXEcole PolytechniquePalaiseau cedexFrance

Personalised recommendations