Article thumbnail

TT2NE: a novel algorithm to predict RNA secondary structures with pseudoknots

By Michaël Bon and Henri Orland

Abstract

We present TT2NE, a new algorithm to predict RNA secondary structures with pseudoknots. The method is based on a classification of RNA structures according to their topological genus. TT2NE is guaranteed to find the minimum free energy structure regardless of pseudoknot topology. This unique proficiency is obtained at the expense of the maximum length of sequences that can be treated, but comparison with state-of-the-art algorithms shows that TT2NE significantly improves the quality of predictions. Analysis of TT2NE's incorrect predictions sheds light on the need to study how sterical constraints limit the range of pseudoknotted structures that can be formed from a given sequence. An implementation of TT2NE on a public server can be found at http://ipht.cea.fr/rna/tt2ne.php

Topics: Methods Online
Publisher: Oxford University Press
OAI identifier: oai:pubmedcentral.nih.gov:3152363
Provided by: PubMed Central

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.

Suggested articles

Citations

  1. (1978). Algorithms for loop matchings.
  2. (1988). Characterization of self-cleaving RNA sequences on the genome
  3. (1999). How RNA folds.
  4. (2011). Molecular Biology of RNA.
  5. (2009). Most mammalian mRNAs are conserved targets of microRNAs.
  6. (1981). Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information.
  7. (2000). RNA pseudoknot prediction in energy-based models.
  8. (1990). The equilibrium partition function and base pair binding probabilities for RNA secondary structure.
  9. (2010). Topology links RNA secondary structure with global conformation, dynamics, and adaptation.