• DocumentCode
    3519199
  • Title

    Applying Clustering and Phylogeny Analysis to Study Dinoflagellates Based on Sterol Composition

  • Author

    Leblond, Jeffrey D. ; Lasiter, Andrew D. ; Li, Cen ; Logares, Ramiro ; Rengefors, Karin ; Evens, Terence J.

  • Author_Institution
    Dept. of Biol., Middle Tennessee State Univ., Murfreesboro, TN
  • fYear
    2008
  • fDate
    3-5 Nov. 2008
  • Firstpage
    90
  • Lastpage
    97
  • Abstract
    This study examined the sterol compositions of 102 dinoflagellates (including several previously unexamined species) using clustering techniques as a means of determining the relatedness of the organisms. In addition, dinoflagellate sterol-based relationships were compared statistically to dinoflagellate 18S rDNA-based phylogeny relationships using the Mantel test. Our results indicated that the examined dinoflagellates form six clusters based on sterol composition and that several, but not all, dinoflagellate genera that form discrete clusters in the 18S rDNA-based phylogeny share similar sterol compositions. This and other correspondences suggest that the sterol compositions of dinoflagellates are explained, to a certain extent, by the evolutionary history of this lineage.
  • Keywords
    Bayes methods; biology computing; ecology; microorganisms; statistical analysis; Mantel test; clustering; dinoflagellates; phylogeny analysis; sterol composition; Bayesian methods; Biomarkers; Clustering algorithms; Data analysis; Euclidean distance; History; Organisms; Partitioning algorithms; Phylogeny; USA Councils; cluster validation; clustering; dinoflagellate; phylogeny; sterol;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine, 2008. BIBM '08. IEEE International Conference on
  • Conference_Location
    Philadelphia, PA
  • Print_ISBN
    978-0-7695-3452-7
  • Type

    conf

  • DOI
    10.1109/BIBM.2008.16
  • Filename
    4684878