CyloFold: secondary structure prediction including pseudoknots

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CyloFold: secondary structure prediction including pseudoknots

UNLABELLED Computational RNA secondary structure prediction approaches differ by the way RNA pseudoknot interactions are handled. For reasons of computational efficiency, most approaches only allow a limited class of pseudoknot interactions or are not considering them at all. Here we present a computational method for RNA secondary structure prediction that is not restricted in terms of pseudok...

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RNA Secondary Structure Prediction with Simple Pseudoknots

Pseudoknots are widely occurring structural motifs in RNA. Pseudoknots have been shown to be functionally important in different RNAs which play regulatory, catalytic, or structural roles in cells. Current biophysical methods to identify the presence of pseudoknots are extremely time consuming and expensive. Therefore, bioinformatics approaches to accurately predict such structures are highly d...

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HotKnots: heuristic prediction of RNA secondary structures including pseudoknots.

We present HotKnots, a new heuristic algorithm for the prediction of RNA secondary structures including pseudoknots. Based on the simple idea of iteratively forming stable stems, our algorithm explores many alternative secondary structures, using a free energy minimization algorithm for pseudoknot free secondary structures to identify promising candidate stems. In an empirical evaluation of the...

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TurboKnot: rapid prediction of conserved RNA secondary structures including pseudoknots

MOTIVATION Many RNA molecules function without being translated into proteins, and function depends on structure. Pseudoknots are motifs in RNA secondary structures that are difficult to predict but are also often functionally important. RESULTS TurboKnot is a new algorithm for predicting the secondary structure, including pseudoknotted pairs, conserved across multiple sequences. TurboKnot fi...

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ژورنال

عنوان ژورنال: Nucleic Acids Research

سال: 2010

ISSN: 0305-1048,1362-4962

DOI: 10.1093/nar/gkq432