Finding Common RNA Pseudoknot Structures in Polynomial Time

  • Patricia A. Evans
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4009)


This paper presents the first polynomial time algorithm for finding common RNA substructures that include pseudoknots and similar structures. While a more general problem is known to be NP-hard, this algorithm exploits special features of RNA structures to match RNA bonds correctly in polynomial time. Although the theoretical upper bound on the algorithm’s time and space usage is high, the data-driven nature of its computation enables it to avoid computing unnecessary cases, dramatically reducing the actual running time. The algorithm works well in practice, and has been tested on sample RNA structures that include pseudoknots and pseudoknot-like tertiary structures.


Polynomial Time Index Combination Common Substructure Pseudoknot Structure Turnip Yellow Mosaic Virus 
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  1. 1.
    Allali, J., Sagot, M.-F.: A new distance for high level RNA secondary structure comparison. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2(1), 3–14 (2005)CrossRefGoogle Scholar
  2. 2.
    Bafna, V., Muthukrishnan, S., Ravi, R.: Computing similarity between RNA strings. DIMACS Technical Report 96-30 (1996)Google Scholar
  3. 3.
    Brown, J.: The Ribonuclease P Database. Nucleic Acids Research 27, 314 (1999)CrossRefGoogle Scholar
  4. 4.
    Burkard, M., Turner, D., Tinoco, I.: Schematic diagrams of secondary and tertiary structure elements. In: Gesteland, R., Cech, T., Atkins, J. (eds.) The RNA World (2nd edn.), pp. 681–685. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York (1999)Google Scholar
  5. 5.
    Cannone, J., et al.: The comparative RNA web (CRW) site: an online database of comparative sequence and structure information for ribosomal, intron, and other RNAs. BioMed. Central Bioinformatics 3, 15 (2002)Google Scholar
  6. 6.
    Evans, P.: Finding common subsequences with arcs and pseudoknots. In: Crochemore, M., Paterson, M. (eds.) CPM 1999. LNCS, vol. 1645, pp. 270–280. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  7. 7.
    Felden, B., Florentz, C., Giegé, R., Westhof, E.: A central pseudoknotted three-way junction imposes tRNA-like mimicry and the orientation of three 5’ upstream pseudoknots in the 3’ terminus of tobacco mosaic virus RNA. RNA 2, 201–212 (1996)Google Scholar
  8. 8.
    Goldman, D., Istrail, S., Papadimitriou, C.: Algorithmic aspects of protein similarity. In: Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS 1999) (1999)Google Scholar
  9. 9.
    Gramm, J.: A polynomial-time algorithm for the matching of crossing contact map patterns. IEEE/ACM Transactions on Computational Biology and Bioinformatics 1(4), 171–180 (2004)CrossRefMathSciNetGoogle Scholar
  10. 10.
    Skuzeski, J., Bozarth, C., Dreher, T.: The turnip yellow mosaic virus tRNA-like structure cannot be replaced by generic tRNA-like elements or by heterologuous 3’ untranslated regions known to enhance mRNA expression and stability. Journal of Virology 70, 2107–2115 (1996)Google Scholar
  11. 11.
    Vialette, S.: On the computational complexity of 2-interval pattern matching problems. Theoretical Computer Science 312(2-3), 223–249 (2004)CrossRefMathSciNetzbMATHGoogle Scholar
  12. 12.
    Zhang, K.: Computing similarity between RNA secondary structures. In: Proceedings of IEEE International Joint Symposia on Intelligence and Systems, pp. 126–132 (1998)Google Scholar
  13. 13.
    Zhang, K., Wang, L., Ma, B.: Computing Similarity between RNA Structures. In: Crochemore, M., Paterson, M. (eds.) CPM 1999. LNCS, vol. 1645, pp. 281–293. Springer, Heidelberg (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Patricia A. Evans
    • 1
  1. 1.Faculty of Computer ScienceUniversity of New BrunswickFrederictonCanada

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