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Int. J. Mol. Sci. 2013, 14(4), 8393-8405; doi:10.3390/ijms14048393
Article

A Convolutional Code-Based Sequence Analysis Model and Its Application

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Received: 19 February 2013; in revised form: 28 March 2013 / Accepted: 10 April 2013 / Published: 16 April 2013
(This article belongs to the Section Biochemistry, Molecular Biology and Biophysics)
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Abstract: A new approach for encoding DNA sequences as input for DNA sequence analysis is proposed using the error correction coding theory of communication engineering. The encoder was designed as a convolutional code model whose generator matrix is designed based on the degeneracy of codons, with a codon treated in the model as an informational unit. The utility of the proposed model was demonstrated through the analysis of twelve prokaryote and nine eukaryote DNA sequences having different GC contents. Distinct differences in code distances were observed near the initiation and termination sites in the open reading frame, which provided a well-regulated characterization of the DNA sequences. Clearly distinguished period-3 features appeared in the coding regions, and the characteristic average code distances of the analyzed sequences were approximately proportional to their GC contents, particularly in the selected prokaryotic organisms, presenting the potential utility as an added taxonomic characteristic for use in studying the relationships of living organisms.
Keywords: convolutional code; degeneracy; codon; informational unit; code distance; characteristic average code distance; GC content; taxonomy convolutional code; degeneracy; codon; informational unit; code distance; characteristic average code distance; GC content; taxonomy
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Liu, X.; Geng, X. A Convolutional Code-Based Sequence Analysis Model and Its Application. Int. J. Mol. Sci. 2013, 14, 8393-8405.

AMA Style

Liu X, Geng X. A Convolutional Code-Based Sequence Analysis Model and Its Application. International Journal of Molecular Sciences. 2013; 14(4):8393-8405.

Chicago/Turabian Style

Liu, Xiao; Geng, Xiaoli. 2013. "A Convolutional Code-Based Sequence Analysis Model and Its Application." Int. J. Mol. Sci. 14, no. 4: 8393-8405.


Int. J. Mol. Sci. EISSN 1422-0067 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert