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

Author: 

Anderson, J
Haas, P
Mathieson, L
Volynkin, V
Lyngsø, R
Tataru, P
Hein, J

Publication Date: 

8 February 2013

Journal: 

Bioinformatics (Oxford, England)

Last Updated: 

2021-04-10T10:57:58.397+01:00

Issue: 

6

Volume: 

29

DOI: 

10.1093/bioinformatics/btt050

page: 

704-710

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.

Symplectic id: 

384144

Submitted to ORA: 

Submitted

Publication Type: 

Journal Article