DocumentCode :
3200494
Title :
Visualization of the sets of DNA sequences using self organizing maps based on correlation coefficients
Author :
Dozono, Hiroshi ; Niina, Gen
Author_Institution :
Dept. of Adv. Technol. Fusion, Saga Univ., Saga, Japan
fYear :
2013
fDate :
18-21 Dec. 2013
Firstpage :
27
Lastpage :
29
Abstract :
Recently, Next Generation Sequencing(NGS) techniques produces huge amount of sequence data day by day. To analyze the sequence data, the efficient method which can handle large amount of data is required. Self Organizing Map (SOM), which uses the frequencies of N-tuples, can categorize the set of DNA sequences with unsupervised learning. In this paper, SOM which uses the correlation coefficient among the nucleotides is proposed, and the performance is examined in the experiments of mapping the genome sequences of several species.
Keywords :
DNA; data visualisation; genomics; molecular biophysics; self-organising feature maps; unsupervised learning; DNA sequence data; N-tuple frequencies; SOM; correlation coefficients; data visualization; genome sequences; next generation sequencing techniques; nucleotides; self organizing maps; unsupervised learning; Bioinformatics; Correlation; DNA; Genomics; Neurons; Sequential analysis; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
Conference_Location :
Shanghai
Type :
conf
DOI :
10.1109/BIBM.2013.6732749
Filename :
6732749
Link To Document :
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