Extracting Common Motifs under the Levenshtein Measure: Theory and Experimentation
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Using our techniques for extracting approximate non-tandem repeats 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 for Edit distance on some real sequences. Her method has not been implemented before for Edit distance but only for Hamming distance,. Our resulting method turns out to be simpler and more efficient theoretically and also in practice for moderately large P and D.
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