DocumentCode :
951419
Title :
LPC cepstral distortion measure for protein sequence comparison
Author :
Pham, Tuan D.
Author_Institution :
Sch. of Inf. Technol., James Cook Univ. of North Queensland, Townsville, Qld., Australia
Volume :
5
Issue :
2
fYear :
2006
fDate :
6/1/2006 12:00:00 AM
Firstpage :
83
Lastpage :
88
Abstract :
Protein sequence comparison is the most powerful tool for the inference of novel protein structure and function. This type of inference is commonly based on the similar sequence-similar structure-similar function paradigm, and derived by sequence similarity searching on databases of protein sequences. As entire genomes have been being determined at a rapid rate, computational methods for comparing protein sequences will be more essential for probing the complexity of molecular machines. In this paper we introduce a pattern-comparison algorithm, which is based on the mathematical concepts of linear predictive coding (LPC) and LPC cepstral distortion measure, for computing similarities/dissimilarities between protein sequences. Experimental results on a real data set of functionally related and functionally nonrelated protein sequences have shown the effectiveness of the proposed approach on both accuracy and computational efficiency.
Keywords :
biology computing; genetics; linear predictive coding; molecular biophysics; molecular configurations; proteins; LPC cepstral distortion measure; genomes; linear predictive coding; pattern-comparison algorithm; protein function; protein sequence comparison; protein structure; Bioinformatics; Cepstral analysis; Computational biology; Computational efficiency; Databases; Distortion measurement; Genomics; Linear predictive coding; Protein sequence; Sequences; Distortion measure; linear predictive coding (LPC); protein sequence comparison; Algorithms; Computer Simulation; Linear Models; Models, Chemical; Models, Molecular; Pattern Recognition, Automated; Proteins; Sequence Alignment; Sequence Analysis, Protein;
fLanguage :
English
Journal_Title :
NanoBioscience, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1241
Type :
jour
DOI :
10.1109/TNB.2006.875029
Filename :
1637448
Link To Document :
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