Using permutation patterns for content-based phylogeny

  • Authors:
  • Md Enamul Karim;Laxmi Parida;Arun Lakhotia

  • Affiliations:
  • Center for Advanced Computer Studies, University of Louisiana at Lafayette;Computational Biology Center, IBM T J Watson Research Center, Yorktown Heights;Center for Advanced Computer Studies, University of Louisiana at Lafayette

  • Venue:
  • PRIB'06 Proceedings of the 2006 international conference on Pattern Recognition in Bioinformatics
  • Year:
  • 2006

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Abstract

When the same set of genes appear in different orders on the chromosomes, they form a permutation pattern. Permutation patterns have been used to identify potential haplogroups in mammalian data [8]. They also have been successfully used to detect phylogenetic relationships between computer viruses [9]. In this paper we explore the use of these patterns as a content similarity measure and use this in inferring phylogenies from genome rearrangement data in polynomial time. The method uses a function of the cardinality of the set of common maximal permutation patterns as a proxy for evolutionary “proximity” between genomes. We introduce Pi-logen, a phylogeny tool based on this method. We summarize results of feasibility study for this scheme on synthetic data by (1) content verification and (2) ancestor prediction. We also successfully infer phylogenies on series of synthetic data and on chloroplast gene order of Campanulaceae data.