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. © The Author 2013.

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Anderson, J. W. J., Haas, P. A., Mathieson, L. A., Volynkin, V., Lyngso, R., Tataru, P., & Hein, J. (2013). Oxfold: Kinetic folding of RNA using stochastic context-free grammars and evolutionary information. Bioinformatics, 29(6), 704–710. https://doi.org/10.1093/bioinformatics/btt050

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