New Distances for Improving Progressive Alignment Algorithm

  • Ahmed Mokaddem
  • Mourad Elloumi
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 177)


Distance computation between sequences is an important method to compare between biological sequences. In fact, we attribute a value to the sequences in order to estimate a percentage of similarity that can help to extract structural or functional information. Distance computation is also more important in the progressive multiple alignment algorithm. Indeed, it can influence the branching order of the sequences alignment and then the final multiple alignment. In this paper, we present new methods for distance computation in order to improve the progressive multiple alignment approach. The main difference between our distances and the other existed methods consists in the use of all the sequences of the set in the pair-wise comparison. We tested our distances on BALIBASE benchmarks and we compared with other typical distances. We obtained very good results.


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Laboratory of Technologies of Information and Communication and Electrical Engineering (LaTICE), Higher School of Sciences and Technologies of Tunis (HSSTT)University of TunisTunisTunisia

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