[Comparison study on the methods for finding borders between coding and non-coding DNA regions in rice].
Entropy-based divergence measures have provided an impelling tool in evaluating sequence complexity, predicting CpG island, and detecting borders between coding and non-coding DNA regions etc. In this paper, two new divergence measures: the alpha-KL divergence and the alpha-Jensen-Shannon divergence were defined and a coarse-graining vector of amino acids- corresponding codons was proposed according to codons GC-content, in order to improve the computational approach to finding borders between coding and non-coding in rice. A comparison of the accuracies gained by different vectors (the Jensen-Shannon divergence, the Jensen-Renyi divergence, the alpha-KL divergence and the alpha-Jensen -Shannon divergence) showed that recognition efficiency based on the new information measures with the vector coarse-graining increase by 4-5 times than that of Bernaola's method in the 'stop codon' of coding regions in rice.
Sun
Yi-Gang
YG
Department of Mathematics, Zhejiang University, Hangzhou 310027, China.
Gao
Lei
L
Zhang
Zhong-Hua
ZH
Xue
Qing-Zhong
QZ
D000465:Algorithms; D000596:Amino Acids / Q000235:genetics; D001482:Base Composition; D003062:Codon / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D018744:DNA, Plant / Q000235:genetics; D005815:Genetic Code; D016366:Open Reading Frames / Q000235:genetics*; D012275:Oryza / Q000235:genetics*
D000596:Amino Acids; D003062:Codon; D018744:DNA, Plant