Local exact pattern matching for non-fixed RNA structures

Authors:
Mika Amit;Rolf Backofen;Steffen Heyne;Gad M. Landau;Mathias Möhl;Christina Schmiedl;Sebastian Will
Affiliations:
Department of Computer Science, University of Haifa, Haifa, Israel;Bioinformatics, Institute of Computer Science, Albert-Ludwigs-Universität, Freiburg, Germany,Center for Biological Signaling Studies (BIOSS), Albert-Ludwigs-Universität, Freiburg, German ...;Bioinformatics, Institute of Computer Science, Albert-Ludwigs-Universität, Freiburg, Germany;Department of Computer Science, University of Haifa, Haifa, Israel,Department of Computer Science and Engineering, NYU-Poly, Brooklyn, NY;Bioinformatics, Institute of Computer Science, Albert-Ludwigs-Universität, Freiburg, Germany;Bioinformatics, Institute of Computer Science, Albert-Ludwigs-Universität, Freiburg, Germany;Bioinformatics, Institute of Computer Science, Albert-Ludwigs-Universität, Freiburg, Germany,CSAIL and Mathematics Department, MIT, Cambridge, MA
Venue:
CPM'12 Proceedings of the 23rd Annual conference on Combinatorial Pattern Matching
Year:
2012

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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(n3) algorithm for local exact pattern matching between two nested RNAs, and an O(n3logn) algorithm for one nested RNA and one bounded-unlimited RNA.