Extracting Common Motifs under the Levenshtein Measure: Theory and Experimentation

  • Ezekiel F. Adebiyi
  • Michael Kaufmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2452)


Using our techniques for extracting approximate non-tandem repeats[1] on well constructed maximal models, we derive an algorithm to find common motifs of length P that occur in N sequences with at most D differences under the Edit distance metric. We compare the effectiveness of our algorithm with the more involved algorithm of Sagot[17] for Edit distance on some real sequences. Her method has not been implemented before for Edit distance but only for Hamming distance[12],[20]. Our resulting method turns out to be simpler and more efficient theoretically and also in practice for moderately large P and D.


Edit Distance Maximal Repeat Distinct Sequence Common Motif Input String 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Ezekiel F. Adebiyi
    • 1
  • Michael Kaufmann
    • 1
  1. 1.Wilhelm-Schickard-Institut für InformatikUniversität TübingenTübingenGermany

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