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

نویسندگان

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

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. 1998 ACM Subject Classification E.1 Data Structures, F.2.2 Nonnumerical Algorithms and Problems

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تاریخ انتشار 2017