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CSB
2003
IEEE

Statistical Inference for Well-ordered Structures in Nucleotide Sequences

13 years 9 months ago
Statistical Inference for Well-ordered Structures in Nucleotide Sequences
Distinct, local structures are frequently correlated with functional RNA elements involved in posttranscriptional regulation of gene expression. Discovery of microRNAs (miRNAs) suggests that there are a large class of small non-coding RNAs in eukaryotic genomes. These miRNAs have the potential to form distinct fold-back stem-loop structures. The prediction of those well-ordered folding sequences (WFS) in genomic sequences is very helpful for our understanding of RNA-based gene regulation and the determination of local RNA elements with structure-dependent functions. In this study, we describe a novel method for discovering the local WFS in a nucleotide sequence by Monte Carlo simulation and RNA folding. In the approach the quality of a local WFS is assessed by the energy difference (Ediff) between the optimal structure folded in the local segment and its corresponding optimal, restrained structure where all the previous base pairings formed in the optimal structure are prohibited. Dis...
Shu-Yun Le, Jih-H. Chen, Jacob V. Maizel
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where CSB
Authors Shu-Yun Le, Jih-H. Chen, Jacob V. Maizel
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