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
Link To Document :
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