DocumentCode
3048063
Title
Notice of Retraction
Finding Borders Between Coding and Noncoding DNA Regions By β-KL Divergence
Author
Jing-Xiang Zhang ; Zhen-Yuan Xu
Author_Institution
Sch. of Sci., Southern Yangtze Univ., Wuxi
fYear
2007
fDate
6-8 July 2007
Firstpage
286
Lastpage
289
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this study we present a new method to denoting DNA sequences based on the distributions of "stop-codon" and "reverse complementation stop-codon"(R14). Using the theory of Shannon entropy, we ameliorate the measure of the Jensen- Shannon divergence and beta - KL divergence, And we compare experimentation obtained by our method with the previous results, Show that recognition efficiency based on the new measures beta - KL divergence with the vector R14 rise 86%, And more than that of by Bernaola\´s meathods presented 70%.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this study we present a new method to denoting DNA sequences based on the distributions of "stop-codon" and "reverse complementation stop-codon"(R14). Using the theory of Shannon entropy, we ameliorate the measure of the Jensen- Shannon divergence and beta - KL divergence, And we compare experimentation obtained by our method with the previous results, Show that recognition efficiency based on the new measures beta - KL divergence with the vector R14 rise 86%, And more than that of by Bernaola\´s meathods presented 70%.
Keywords
DNA; biology computing; encoding; genetics; molecular biophysics; β - KL divergence; DNA sequences; Jensen-Shannon divergence; Shannon entropy; coding regions; recognition efficiency; reverse complementation stop-codon; stop-codon distributions; Amino acids; Bioinformatics; DNA; Entropy; Genomics; Information technology; Sequences; Signal detection; Signal processing; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on
Conference_Location
Wuhan
Print_ISBN
1-4244-1120-3
Type
conf
DOI
10.1109/ICBBE.2007.77
Filename
4272561
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