Paper Info
Title
glu-RNA: aliGn highLy strUctured ncRNAs using only sequence similarity
Abstract
Generating reliable alignments for ncRNAs is an important step in ncRNA secondary structure prediction and ncRNA gene finding. Existing sequence alignment programs can generate reliable alignments for ncRNAs with high sequence conservation. For highly structured ncRNAs that may lack strong sequence similarity, structural alignment programs are required. However, conducting reliable structural alignment is much more expensive than sequence alignment and is not ideal for large-scale input such as whole genomes or next-generation sequencing data. In this paper, we propose an accurate ncRNA alignment approach to align highly structured ncRNAs using only sequence similarity. By incorporating posterior probability and a machine learning approach, we can generate accurate alignments of highly structured ncRNAs without using structural information. We tested our approach on over three hundreds of pairs of highly structured ncRNAs from BRAliBase 2.1. The experimental results show that our approach can achieve more accurate alignments than commonly used sequence alignment programs and a popular structural alignment tool. The source codes of glu-RNA can be downloaded at http://sourceforge.net/projects/glu-rna/.
Year
DOI
Venue
2013
10.1145/2506583.2506617
BCB
Keywords
Field
DocType
accurate alignment,sequence alignment,sequence alignment program,sequence similarity,reliable structural alignment,accurate ncrna alignment approach,existing sequence alignment program,structural alignment program,reliable alignment,align highly structured ncrnas,generating reliable alignment,popular structural alignment tool
Sequence alignment,Structural alignment,Alignment-free sequence analysis,Computer science,Source code,Gene prediction,Posterior probability,Bioinformatics,Multiple sequence alignment,Non-coding RNA
Conference
Citations 
PageRank 
References 
0
0.34
16
Authors
2
Name
Order
Citations
PageRank
Prapaporn Techa-Angkoon122.08
Yanni Sun221921.16