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Local Exact Pattern Matching for Non-fixed RNA Structures

  • Mika Amit
  • Rolf Backofen
  • Steffen Heyne
  • Gad M. Landau
  • Mathias Möhl
  • Christina Schmiedl
  • Sebastian Will
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7354)

Abstract

Detecting local common sequence-structure regions of RNAs is a biologically meaningful problem. By detecting such regions, biologists are able to identify functional similarity between the inspected molecules. We developed dynamic programming algorithms for finding common structure-sequence patterns between two RNAs. The RNAs are given by their sequence and a set of potential base pairs with associated probabilities. In contrast to prior work which matches fixed structures, we support the arc breaking edit operation; this allows to match only a subset of the given base pairs. We present an O(n 3) algorithm for local exact pattern matching between two nested RNAs, and an O(n 3logn) algorithm for one nested RNA and one bounded-unlimited RNA.

Keywords

Base Pair Time Complexity Maximal Match Edit Operation Tree Edit Distance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mika Amit
    • 1
  • Rolf Backofen
    • 3
    • 4
  • Steffen Heyne
    • 3
  • Gad M. Landau
    • 1
    • 2
  • Mathias Möhl
    • 3
  • Christina Schmiedl
    • 3
  • Sebastian Will
    • 3
    • 5
  1. 1.Department of Computer ScienceUniversity of HaifaHaifaIsrael
  2. 2.Department of Computer Science and EngineeringNYU-PolyBrooklynUSA
  3. 3.Bioinformatics, Institute of Computer ScienceAlbert-Ludwigs-UniversitätFreiburgGermany
  4. 4.Center for Biological Signaling Studies (BIOSS)Albert-Ludwigs-UniversitätFreiburgGermany
  5. 5.CSAIL and Mathematics DepartmentMITCambridgeUSA

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