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Using Gaussian model to improve biological sequence comparison.

Authors :
QI DAI
XIAOQING LIU
LIHUA LI
YUHUA YAO
BIN HAN
LEI ZHU
Source :
Journal of Computational Chemistry. 1/30/2010, Vol. 31 Issue 2, p351-361. 11p. 1 Diagram, 3 Charts, 5 Graphs.
Publication Year :
2010

Abstract

One of the major tasks in biological sequence analysis is to compare biological sequences, which could serve as evidence of structural and functional conservation, as well as of evolutionary relations among the sequences. Numerous efficient methods have been developed for sequence comparison, but challenges remain. In this article, we proposed a novel method to compare biological sequences based on Gaussian model. Instead of comparing the frequencies of k-words in biological sequences directly, we considered the k-word frequency distribution under Gaussian model which gives the different expression levels of k-words. The proposed method was tested by similarity search, evaluation on functionally related genes, and phylogenetic analysis. The performance of our method was further compared with alignment-based and alignment-free methods. The results demonstrate that Gaussian model provides more information about k-word frequencies and improves the efficiency of sequence comparison. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010 [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01928651
Volume :
31
Issue :
2
Database :
Academic Search Index
Journal :
Journal of Computational Chemistry
Publication Type :
Academic Journal
Accession number :
46757790
Full Text :
https://doi.org/10.1002/jcc.21322