TITLE

Cardioviral RNA structure logo analysis: entropy, correlations, and prediction

AUTHOR(S)
Xiao-Zhou Chen; Huai Cao; Wen Zhang; Ci-Quan Liu
PUB. DATE
March 2010
SOURCE
Journal of Biological Physics;Mar2010, Vol. 36 Issue 2, p145
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
In recent years, there has been an increased number of sequenced RNAs leading to the development of new RNA databases. Thus, predicting RNA structure from multiple alignments is an important issue to understand its function. Since RNA secondary structures are often conserved in evolution, developing methods to identify covariate sites in an alignment can be essential for discovering structural elements. Structure Logo is a technique established on the basis of entropy and mutual information measured to analyze RNA sequences from an alignment. We proposed an efficient Structure Logo approach to analyze conservations and correlations in a set of Cardioviral RNA sequences. The entropy and mutual information content were measured to examine the conservations and correlations, respectively. The conserved secondary structure motifs were predicted on the basis of the conservation and correlation analyses. Our predictive motifs were similar to the ones observed in the viral RNA structure database, and the correlations between bases also corresponded to the secondary structure in the database.
ACCESSION #
48191100

 

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