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

作者：Anderson James W J^*; Haas Pierre A; Mathieson Leigh Anne; Volynkin Vladimir; Lyngso Rune; Tataru Paula; Hein Jotun

来源：Bioinformatics, 2013, 29(6): 704-710.

DOI：10.1093/bioinformatics/btt050

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. %26lt;br%26gt;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. %26lt;br%26gt;Availability: http://www.stats.ox.ac.uk/similar to anderson. %26lt;br%26gt;Contact: [e-mail] %26lt;br%26gt;Supplementary information: Supplementary data are available at Bioinformatics online.

• 出版日期2013-3-15