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A Bioinformatics-Inspired Adaptation to Ukkonen’s Edit Distance Calculating Algorithm and Its Applicability Towards Distributed Data Mining
University of Tennessee
- 1 University of Tennessee
Journal of Software Engineering and Applications·Volume 01 (2008)·Pages 8–12·Published 9 December 2008·DOI10.4236/jsea.2008.11002
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Abstract
Edit distance measures the similarity between two strings (as the minimum number of change, insert or delete operations that transform one string to the other). An edit sequence s is a sequence of such operations and can be used to represent the string resulting from applying s to a reference string. We present a modification to Ukkonen’s edit distance calculating algorithm based upon representing strings by edit sequences. We conclude with a demonstration of how using this representation can improve mitochondrial DNA query throughput performance in a distributed computing environment.
KeywordsBioinformatics-Inspired AdaptationCalculating AlgorithmData Mining
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