DocumentCode :
3509705
Title :
Clustering of Positions in Nucleotide Sequences by Trim Distance
Author :
Shimada, Toshikazu ; Hamada, Issei ; Hirata, Kazufumi ; Kuboyama, Tetsuji ; Yonezawa, Keishi ; Ito, Kei
Author_Institution :
Kyushu Inst. of Technol., Iizuka, Japan
fYear :
2013
fDate :
Aug. 31 2013-Sept. 4 2013
Firstpage :
129
Lastpage :
134
Abstract :
A trim distance is a measure for comparing positions in nucleotide sequences based on phylogenetic trees. In this paper, first we formulate another trim distance based on the MAST distance, in contrast to the previous trim distance based on the LCA-preserving distance. Next, we apply a group average method in agglomerative hierarchical clustering to the positions in nucleotide sequences by the trim distances to nucleotide sequences of influenza A (H1N1) viruses at 2008 as non-pandemic viruses and at 2009 as pandemic viruses, with introducing the following two methods of clustering. The clustering of separated positions is one method of clustering whose positions in nucleotide sequences at 2008 are separated from those at 2009. The clustering of mixed positions is another method of clustering whose positions in nucleotide sequences at 2008 are mixed with those at 2009.
Keywords :
bioinformatics; pattern clustering; sequences; LCA-preserving distance; MAST distance; agglomerative hierarchical clustering; group average method; influenza; nonpandemic viruses; nucleotide sequences; pandemic viruses; phylogenetic trees; trim distance; Informatics; LCA-preserving distance; MAST distace; clustering; nucleotide sequence; trim distance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Applied Informatics (IIAIAAI), 2013 IIAI International Conference on
Conference_Location :
Los Alamitos, CA
Print_ISBN :
978-1-4799-2134-8
Type :
conf
DOI :
10.1109/IIAI-AAI.2013.72
Filename :
6630332
Link To Document :
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