Skip to main content

Seed-Based Exclusion Method for Non-coding RNA Gene Search

  • Conference paper
Computing and Combinatorics (COCOON 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4598))

Included in the following conference series:

  • 979 Accesses

Abstract

Given an RNA family characterized by conserved sequences and folding constraints, the problem is to search for all the instances of the RNA family in a genomic database. As seed-based heuristics have been proved very efficient to accelerate the classical homology based search methods such as BLAST, we use a similar idea for RNA structures. We present an exclusion method for RNA search allowing for possible nucleotide insertion, deletion and substitution. It is based on a partition of the RNA stem-loops into consecutive seeds and a preprocessing of the target database. This algorithm can be used to improve time efficiency of current methods, and is guaranteed to find all occurrences that contain at least one exact seed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J.: Basic local alignment search tool. Journal of Molecular Biology 215, 403–410 (1990)

    Google Scholar 

  2. Bafna, V., Zhang, S.: FastR: Fast database search tool for non-coding RNA. In: Proceedings of IEEE Computational Systems Bioinformatics (CSB) Conference, pp. 52–61 (2004)

    Google Scholar 

  3. Eddy, S.R.: RNABOB: a program to search for RNA secondary structure motifs in sequence databases (1992), http://bioweb.pasteur.fr/docs/man/man/rnabob.1.html#toc1

  4. El-Mabrouk, N., Lisacek, F.: Very fast identification of RNA motifs in genomic DNA. Application to tRNA search in the yeast genome. Journal of Molecular Biology 264, 46–55 (1996)

    Article  Google Scholar 

  5. El-Mabrouk, N., Raffinot, M., Duchesne, J.E., Lajoie, M., Luc, N.: Approximate matching of structured motifs in DNA sequences. J. Bioinformatics and Computational Biology 3(2), 317–342 (2005)

    Article  Google Scholar 

  6. Fichant, G.A., Burks, C.: Identifying potential tRNA genes in genomic DNA sequences. Journal of Molecular Biology 220, 659–671 (1991)

    Article  Google Scholar 

  7. Gautheret, D., Major, F., Cedergren, R.: Pattern searching/alignment with RNA primary and secondary structures. Comput. Appl. Biosci. 6(4), 325–331 (1990)

    Google Scholar 

  8. Klein, R., Eddy, S.: RESEARCH: Finding homologs of single structured RNA sequences (2003)

    Google Scholar 

  9. Laslett, D., Canback, B.: ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. Nucleic Acids Research 32, 11–16 (2004)

    Article  Google Scholar 

  10. Li, M., Ma, B., Kisman, D., Tromp, J.: PatternHunter II: Highly Sensitive and Fast Homology Search. Journal of Bioinformatics and Computational Biology 2(3), 417–439 (2004) Early version in GIW 2003

    Article  Google Scholar 

  11. Ma, B., Tromp, J., Li, M.: PatternHunter: faster and more sensitive homology search. Bioinformatics 18(3), 440–445 (2002)

    Article  Google Scholar 

  12. Macke, T., Ecker, D., Gutell, R., Gautheret, D., Case, D.A., Sampath, R.: RNAmotif – a new RNA secondary structure definition and discovery algorithm. Nucleic Acids Research 29, 4724–4735 (2001)

    Article  Google Scholar 

  13. Rivas, E., Eddy, S.R.: Secondary Structure Alone is Generally Not Statistically Significant for the Detection of Noncoding RNAs. Bioinformatics 16(7), 583–605 (2000)

    Article  Google Scholar 

  14. Robin, S., Daudin, J.-J., Richard, H., Sagot, M.-F., Schbath, S.: Occurrence probability of structured motifs in random sequences. J. Comp. Biol. 9, 761–773 (2002)

    Article  Google Scholar 

  15. Sagot, M.F., Viari, A.: Flexible identification of structural objects in nucleic acid sequences: palindromes, mirror repeats, pseudoknots and triple helices. In: Hein, J., Apostolico, A. (eds.) Combinatorial Pattern Matching. LNCS, vol. 1264, pp. 224–246. Springer, Heidelberg (1997)

    Google Scholar 

  16. Zhang, S., Borovok, I., Aharonovitz, Y., Sharan, R., Bafna, V.: A sequence-based filtering method for ncRNA identification and its application to searching for riboswitch elements. Bioinformatics 22(14), e557–e565 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Guohui Lin

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Duchesne, JE., Giraud, M., El-Mabrouk, N. (2007). Seed-Based Exclusion Method for Non-coding RNA Gene Search. In: Lin, G. (eds) Computing and Combinatorics. COCOON 2007. Lecture Notes in Computer Science, vol 4598. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73545-8_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-73545-8_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73544-1

  • Online ISBN: 978-3-540-73545-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics