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Updated: Aug 14, 2026

RNA Secondary Structure Prediction Using High-throughput SHAPE
Published on: May 31, 2013
BayesFold: rational 2 degrees folds that combine thermodynamic, covariation, and chemical data for aligned RNA
Rob Knight1, Amanda Birmingham, Michael Yarus
1Department of Molecular, Cellular, and Developmental Biology, Campus Box 347, University of Colorado, Boulder 80309, USA.
Abstract:
BayesFold is a Web application that folds an alignment of closely related sequences and evaluates hypotheses about their shared structure. It uses Bayes's Theorem to combine information from several sources, including chemical mapping (if available), thermodynamic folding, and observed sequence variations. Its method provides a rational basis for integrating results, even when these methods conflict. On a gapped alignment of 86 tRNAPhe sequences each 77 bases long, BayesFold takes 31 sec to perform the calculations; the best structure contained 95% of the base pairs in the true structure, and the true structure was ranked second. Notably, similar results come from random samples of only 10 sequences from the alignment (running time 3 sec), suggesting that remarkably few sequences are required for good results. In contrast, folding single sequences with BayesFold produced structures 9.6 bp different, or with the Vienna package, 13.4 bp different, from the true structure. Similar results were obtained for other families of tRNAs. We especially recommend BayesFold for alignments of 3-50 closely related sequences, such as the sequence families frequently found in SELEX. In addition to providing a convenient way to explore the effects of each of the criteria on the plausibility of different structures, BayesFold also makes it easy to produce publication-quality secondary-structure graphics. The Web interface, available at http://bayes.colorado.edu/fold/, includes the flexibility to thread any of the sequences (or the consensus sequence) through any of the structures, including the one judged most probable.
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