title: PicXAA-R: efficient structural alignment of multiple RNA sequences using a greedy approach.
abstract: BACKGROUND
  Accurate and efficient structural alignment of non-coding RNAs (ncRNAs) has grasped more and more attentions as recent studies unveiled the significance of ncRNAs in living organisms. While the Sankoff style structural alignment algorithms cannot efficiently serve for multiple sequences, mostly progressive schemes are used to reduce the complexity. However, this idea tends to propagate the early stage errors throughout the entire process, thereby degrading the quality of the final alignment. For multiple protein sequence alignment, we have recently proposed PicXAA which constructs an accurate alignment in a non-progressive fashion.
  
  
  RESULTS
  Here, we propose PicXAA-R as an extension to PicXAA for greedy structural alignment of ncRNAs. PicXAA-R efficiently grasps both folding information within each sequence and local similarities between sequences. It uses a set of probabilistic consistency transformations to improve the posterior base-pairing and base alignment probabilities using the information of all sequences in the alignment. Using a graph-based scheme, we greedily build up the structural alignment from sequence regions with high base-pairing and base alignment probabilities.
  
  
  CONCLUSIONS
  Several experiments on datasets with different characteristics confirm that PicXAA-R is one of the fastest algorithms for structural alignment of multiple RNAs and it consistently yields accurate alignment results, especially for datasets with locally similar sequences. PicXAA-R source code is freely available at: http://www.ece.tamu.edu/~bjyoon/picxaa/.
authors.affiliation: Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA. msahraeian@tamu.edu
authors.forename: Sayed Mohammad Ebrahim
authors.initials: SM
authors.lastname: Sahraeian
authors.forename: Byung-Jun
authors.initials: BJ
authors.lastname: Yoon
mesh_terms: D000465:Algorithms; D020029:Base Pairing; D019295:Computational Biology / Q000379:methods; D015233:Models, Statistical; D022661:RNA, Untranslated / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D017423:Sequence Analysis, RNA / Q000379:methods*
chemical_list: D022661:RNA, Untranslated