ArticleBMC bioinformatics2007
Can Clustal-style progressive pairwise alignment of multiple sequences be used in RNA secondary structure prediction?
Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- RNA structure replaces the need for U2AF2 in splicing.Genome research · 2016Article
- Multilign: an algorithm to predict secondary structures conserved in multiple RNA sequences.Bioinformatics (Oxford, England) · 2011Article
- Folding and finding RNA secondary structure.Cold Spring Harbor perspectives in biology · 2010Review
- ConStruct: Improved construction of RNA consensus structures.BMC bioinformatics · 2008Article
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2 authors.
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Abstract
backgroundIn ribonucleic acid (RNA) molecules whose function depends on their final, folded three-dimensional shape (such as those in ribosomes or spliceosome complexes), the secondary structure, defined by the set of internal basepair interactions, is more consistently conserved than the primary structure, defined by the sequence of nucleotides.
resultsThe research presented here investigates the possibility of applying a progressive, pairwise approach to the alignment of multiple RNA sequences by simultaneously predicting an energy-optimized consensus secondary structure. We take an existing algorithm for finding the secondary structure common to two RNA sequences, Dynalign, and alter it to align profiles of multiple sequences. We then explore the relative successes of different approaches to designing the tree that will guide progressive alignments of sequence profiles to create a multiple alignment and prediction of conserved structure.
conclusionWe have found that applying a progressive, pairwise approach to the alignment of multiple ribonucleic acid sequences produces highly reliable predictions of conserved basepairs, and we have shown how these predictions can be used as constraints to improve the results of a single-sequence structure prediction algorithm. However, we have also discovered that the amount of detail included in a consensus structure prediction is highly dependent on the order in which sequences are added to the alignment (the guide tree), and that if a consensus structure does not have sufficient detail, it is less likely to provide useful constraints for the single-sequence method.
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