Oxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information

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Abstract

Motivation:

Many computational methods for RNA secondary structure prediction, and, in particular, for the prediction of a consensus structure of an alignment of RNA sequences, have been developed. Most methods, however, ignore biophysical factors, such as the kinetics of RNA folding; no current implementation considers both evolutionary information and folding kinetics, thus losing information that, when considered, might lead to better predictions.

Results:

We present an iterative algorithm, Oxfold, in the framework of stochastic context-free grammars, that emulates the kinetics of RNA folding in a simplified way, in combination with a molecular evolution model. This method improves considerably on existing grammatical models that do not consider folding kinetics. Additionally, the model compares favourably to non-kinetic thermodynamic models.

Availability:

http://www.stats.ox.ac.uk/∼anderson.

Contact:

anderson@stats.ox.ac.uk

Supplementary information:

Supplementary data are available at Bioinformatics online.

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