• DocumentCode
    3230503
  • Title

    Unweighted Multiple Group Method with Arithmetic Mean

  • Author

    Yujian, Li ; Liye, Xu

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Beijing Univ. of Technol., Beijing, China
  • fYear
    2010
  • fDate
    23-26 Sept. 2010
  • Firstpage
    830
  • Lastpage
    834
  • Abstract
    The traditional UPGMA (Unweighted Pair Group Method with Arithmetic Mean) sometimes derives two or more topologies of “tie trees” from a single data set, depending on the order of data entry. This paper presents an improved algorithm for UPGMA, namely, UMGMA (Unweighted Multiple Group Method with Arithmetic Mean), which can produce a unique multifurcating tree from any distance matrix. Moreover, a UMGMA tree has the same topology as its corresponding UPGMA tree if it is actually bifurcating. UMGMA is different from UPGMA in that it repeatedly merges multiple groups into one by the vertices of a maximal θ-distant subtree until only one group is left, so the UMGMA tree is always unique even in the case that the UPGMA tree is not unique.
  • Keywords
    arithmetic; biology computing; molecular biophysics; statistical analysis; UPGMA algorithm; UPGMA tree; distance matrix; multifurcating tree; phylogenetic analysis; unweighted multiple group method with arithmetic mean; unweighted pair group method; Genetics; Phylogenetic analysis; UMGMA; UPGMA; bifurcating tree; multifurcating tree;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-6437-1
  • Type

    conf

  • DOI
    10.1109/BICTA.2010.5645232
  • Filename
    5645232