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

2006

Article

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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 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. 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 to the much slower existing algorithms.

Author(s): Tabei, Y. and Tsuda, K. and Kin, T. and Asai, K.
Journal: Bioinformatics
Volume: 22
Number (issue): 14
Pages: 1723-1729
Year: 2006
Month: May
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Digital: 0
DOI: 10.1093/bioinformatics/btl177
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@article{4070,
  title = {SCARNA: Fast and Accurate Structural Alignment of RNA Sequences by Matching Fixed-Length Stem Fragments},
  author = {Tabei, Y. and Tsuda, K. and Kin, T. and Asai, K.},
  journal = {Bioinformatics},
  volume = {22},
  number = {14},
  pages = {1723-1729},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = may,
  year = {2006},
  month_numeric = {5}
}