• DocumentCode
    110450
  • Title

    Merging Partially Labelled Trees: Hardness and a Declarative Programming Solution

  • Author

    Labarre, Anthony ; Verwer, Sicco

  • Author_Institution
    Lab. d´Inf. Gaspard Monge, Univ. Paris-Est Marne-la-Vallee, Champs-sur-Marne, France
  • Volume
    11
  • Issue
    2
  • fYear
    2014
  • fDate
    March-April 2014
  • Firstpage
    389
  • Lastpage
    397
  • Abstract
    Intraspecific studies often make use of haplotype networks instead of gene genealogies to represent the evolution of a set of genes. Cassens et al. proposed one such network reconstruction method, based on the global maximum parsimony principle, which was later recast by the first author of the present work as the problem of finding a minimum common supergraph of a set of t partially labelled trees. Although algorithms have been proposed for solving that problem on two graphs, the complexity of the general problem on trees remains unknown. In this paper, we show that the corresponding decision problem is NP-complete for t=3. We then propose a declarative programming approach to solving the problem to optimality in practice, as well as a heuristic approach, both based on the idpsystem, and assess the performance of both methods on randomly generated data.
  • Keywords
    DNA; biology computing; decision making; evolution (biological); genetics; heuristic programming; molecular biophysics; trees (mathematics); IDP system; decision problem; declarative programming solution; gene genealogies; gene sets; global maximum parsimony principle; haplotype networks; hardness; merging partially labelled trees; minimum common supergraph; network reconstruction method; randomly generated data; Bioinformatics; Complexity theory; Computational biology; Labeling; Phylogeny; Vegetation; NP-hardness,satsolver, idp; Phylogenetic networks; supergraphs;
  • fLanguage
    English
  • Journal_Title
    Computational Biology and Bioinformatics, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1545-5963
  • Type

    jour

  • DOI
    10.1109/TCBB.2014.2307200
  • Filename
    6746225