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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)

Abstract

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.

Keywords

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

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

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