Abstract
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.
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Adebiyi, E.F., Kaufmann, M. (2002). Extracting Common Motifs under the Levenshtein Measure: Theory and Experimentation. In: Guigó, R., Gusfield, D. (eds) Algorithms in Bioinformatics. WABI 2002. Lecture Notes in Computer Science, vol 2452. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45784-4_11
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DOI: https://doi.org/10.1007/3-540-45784-4_11
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