Prediction of RNA secondary structures with pseudoknots

We present a new algorithm to predict RNA secondary structures with pseudoknots. The method is based on a classification of RNA structures according to their topological genus. The algorithm utilizes a simplified parametrization of the free energies for pair stacking, loop penalties, etc. and in addition a free energy penalty proportional to the topological genus of the pairing graph. Our method can take into account all pseudoknot topologies and achieves high success rates compared to state-of-the-art methods. This shows that the genus is a promising concept to classify pseudoknots.