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

This is the authors' abstract. We don't add key points for this paper.

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.