Fast prediction of RNA-RNA interaction

  • Authors:
  • Raheleh Salari;Rolf Backofen;S. Cenk Sahinalp

  • Affiliations:
  • School of Computing Science, Simon Fraser University, Burnaby, Canada;Bioinformatics Group, Albert-Ludwigs-University, Freiburg, Germany;School of Computing Science, Simon Fraser University, Burnaby, Canada

  • Venue:
  • WABI'09 Proceedings of the 9th international conference on Algorithms in bioinformatics
  • Year:
  • 2009

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Abstract

Regulatory antisense RNAs are a class of ncRNAs that regulate gene expression by prohibiting the translation of an mRNA by establishing stable interactions with a target sequence. There is great demand for efficient computational methods to predict the specific interaction between an ncRNA and its target mRNA(s). There are a number of algorithms in the literature which can predict a variety of such interactions - unfortunately at a very high computational cost. Although some existing target prediction approaches are much faster, they are specialized for interactions with a single binding site. In this paper we present a novel algorithm to accurately predict the minimum free energy structure of RNA-RNA interaction under the most general type of interactions studied in the literature. Moreover, we introduce a fast heuristic method to predict the specific (multiple) binding sites of two interacting RNAs. We verify the performance of our algorithms for joint structure and binding site prediction on a set of known interacting RNA pairs. Experimental results show our algorithms are highly accurate and outperform all competitive approaches.