• DocumentCode
    1340730
  • Title

    On the Elusiveness of Clusters

  • Author

    Kelk, S. ; Scornavacca, C. ; van Iersel, L.

  • Author_Institution
    Dept. of Knowledge Eng. (DKE), Maastricht Univ., Maastricht, Netherlands
  • Volume
    9
  • Issue
    2
  • fYear
    2012
  • Firstpage
    517
  • Lastpage
    534
  • Abstract
    Rooted phylogenetic networks are often used to represent conflicting phylogenetic signals. Given a set of clusters, a network is said to represent these clusters in the softwiredsense if, for each cluster in the input set, at least one tree embedded in the network contains that cluster. Motivated by parsimony we might wish to construct such a network using as few reticulations as possible, or minimizing the level of the network, i.e., the maximum number of reticulations used in any "tangled" region of the network. Although these are NP-hard problems, here we prove that, for every fixed k ≥ 0, it is polynomial-time solvable to construct a phylogenetic network with level equal to k representing a cluster set, or to determine that no such network exists. However, this algorithm does not lend itself to a practical implementation. We also prove that the comparatively efficient CASS algorithm correctly solves this problem (and also minimizes the reticulation number) when input clusters are obtained from two not necessarily binary gene trees on the same set of taxa but does not always minimize level for general cluster sets. Finally, we describe a new algorithm which generates in polynomial-time all binary phylogenetic networks with exactly r reticulations representing a set of input clusters (for every fixed r ≥ 0).
  • Keywords
    biology computing; computational complexity; embedded systems; evolution (biological); genetics; optimisation; CASS algorithm; NP-hard problems; binary gene trees; cluster elusiveness; conflicting phylogenetic signals; least one tree embedded networks; parsimony motivation; polynomial-time solvable networks; reticulation number; rooted phylogenetic networks; softwired sense; tangled region; Binary trees; Clustering algorithms; Generators; Minimization; Phylogeny; Polynomials; Vegetation; Rooted phylogenetic networks; clusters; computational complexity; parsimony; polynomial-time algorithms.; reticulate evolution; Algorithms; Cluster Analysis; Computational Biology; Evolution, Molecular; Models, Genetic; Phylogeny;
  • fLanguage
    English
  • Journal_Title
    Computational Biology and Bioinformatics, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1545-5963
  • Type

    jour

  • DOI
    10.1109/TCBB.2011.128
  • Filename
    6035670