Many 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 statistical methods however ignore biophysical factors such as the kinetics of RNA folding. That way, information is lost that might lead to better predictions.

We present an iterative algorithm, Oxfold, in the framework of stochastic context-free grammars, that emulates the kinetics of RNA folding. The kinetic model performs very well compared to other grammatical models for RNA secondary structure prediction that do not consider folding kinetics.