Journal of Software Engineering and Applications

Volume 1, Issue 1 (December 2008)

ISSN Print: 1945-3116   ISSN Online: 1945-3124

Google-based Impact Factor: 1.22  Citations  h5-index & Ranking

A Bioinformatics-Inspired Adaptation to Ukkonen’s Edit Distance Calculating Algorithm and Its Applicability Towards Distributed Data Mining

HTML  Download Download as PDF (Size: 189KB)  PP. 8-12  
DOI: 10.4236/jsea.2008.11002    6,674 Downloads   10,363 Views  Citations
Author(s)

Affiliation(s)

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.

Share and Cite:

J. Bruce, "A Bioinformatics-Inspired Adaptation to Ukkonen’s Edit Distance Calculating Algorithm and Its Applicability Towards Distributed Data Mining," Journal of Software Engineering and Applications, Vol. 1 No. 1, 2008, pp. 8-12. doi: 10.4236/jsea.2008.11002.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.