title: Predicting pseudoknotted structures across two RNA sequences.
abstract: BACKGROUND
  Laboratory RNA structure determination is demanding and costly and thus, computational structure prediction is an important task. Single sequence methods for RNA secondary structure prediction are limited by the accuracy of the underlying folding model, if a structure is supported by a family of evolutionarily related sequences, one can be more confident that the prediction is accurate. RNA pseudoknots are functional elements, which have highly conserved structures. However, few comparative structure prediction methods can handle pseudoknots due to the computational complexity.
  
  
  RESULTS
  A comparative pseudoknot prediction method called DotKnot-PW is introduced based on structural comparison of secondary structure elements and H-type pseudoknot candidates. DotKnot-PW outperforms other methods from the literature on a hand-curated test set of RNA structures with experimental support.
  
  
  BACKGROUND
  DotKnot-PW and the RNA structure test set are available at the web site http://dotknot.csse.uwa.edu.au/pw.
  
  
  BACKGROUND
  janaspe@csse.uwa.edu.au
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Computer Science and Software Engineering, University of Western Australia, Perth, Australia. janaspe@csse.uwa.edu.au
authors.forename: Jana
authors.initials: J
authors.lastname: Sperschneider
authors.forename: Amitava
authors.initials: A
authors.lastname: Datta
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Wise
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods; D012313:RNA / Q000737:chemistry* / Q000235:genetics; D059370:RNA Folding; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software
chemical_list: D012313:RNA