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  SCARNA: Fast and Accurate Structural Alignment of RNA Sequences by Matching Fixed-Length Stem Fragments

Tabei, Y., Tsuda, K., Kin, T., & Asai, K. (2006). SCARNA: Fast and Accurate Structural Alignment of RNA Sequences by Matching Fixed-Length Stem Fragments. Bioinformatics, 22(14), 1723-1729. doi:10.1093/bioinformatics/btl177.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D1D9-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-8673-3
Genre: Journal Article

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Tabei, Y1, Author              
Tsuda, K1, Author              
Kin, T, Author
Asai, K, Author
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1External Organizations, ou_persistent22              

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 Abstract: Motivation: The functions of non-coding RNAs are strongly related to their secondary structures, but it is known that a secondary structure prediction of a single sequence is not reliable. Therefore, we have to collect similar RNA sequences with a common secondary structure for the analyses of a new non-coding RNA without knowing the exact secondary structure itself. Therefore, the sequence comparison in searching similar RNAs should consider not only their sequence similarities but also their potential secondary structures. Sankoff's algorithm predicts the common secondary structures of the sequences, but it is computationally too expensive to apply to large-scale analyses. Because we often want to compare a large number of cDNA sequences or to search similar RNAs in the whole genome sequences, much faster algorithms are required. Results: We propose a new method of comparing RNA sequences based on the structural alignments of the fixed-length fragments of the stem candidates. The implemented software, SCARNA (Stem Candidate Aligner for RNAs), is fast enough to apply to the long sequences in the large-scale analyses. The accuracy of the alignments is better or comparable with the much slower existing algorithms.

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 Dates: 2006-05
 Publication Status: Published in print
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1093/bioinformatics/btl177
BibTex Citekey: 4070
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Title: Bioinformatics
Source Genre: Journal
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Publ. Info: Oxford : Oxford University Press
Pages: - Volume / Issue: 22 (14) Sequence Number: - Start / End Page: 1723 - 1729 Identifier: ISSN: 1367-4803
CoNE: https://pure.mpg.de/cone/journals/resource/954926969991