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Towards Distance-Based Phylogenetic Inference in Average-Case Linear-Time

Authors Maxime Crochemore, Alexandre P. Francisco, Solon P. Pissis, Cátia Vaz

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Maxime Crochemore
Alexandre P. Francisco
Solon P. Pissis
Cátia Vaz

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Maxime Crochemore, Alexandre P. Francisco, Solon P. Pissis, and Cátia Vaz. Towards Distance-Based Phylogenetic Inference in Average-Case Linear-Time. In 17th International Workshop on Algorithms in Bioinformatics (WABI 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 88, pp. 9:1-9:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)
https://doi.org/10.4230/LIPIcs.WABI.2017.9

Abstract

Computing genetic evolution distances among a set of taxa dominates the running time of many phylogenetic inference methods. Most of genetic evolution distance definitions rely, even if indirectly, on computing the pairwise Hamming distance among sequences or profiles. We propose here an average-case linear-time algorithm to compute pairwise Hamming distances among a set of taxa under a given Hamming distance threshold. This article includes both a theoretical analysis and extensive experimental results concerning the proposed algorithm. We further show how this algorithm can be successfully integrated into a well known phylogenetic inference method.
Keywords
  • computational biology
  • phylogenetic inference
  • Hamming distance

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