Dynamic programming algorithms for RNA secondary structure prediction with pseudoknots
Discrete Applied Mathematics - Special volume on combinatorial molecular biology
BIBE '01 Proceedings of the 2nd IEEE International Symposium on Bioinformatics and Bioengineering
On Approximating an Implicit Cover Problem in Biology
AAIM '09 Proceedings of the 5th International Conference on Algorithmic Aspects in Information and Management
Approximation Algorithms for Predicting RNA Secondary Structures with Arbitrary Pseudoknots
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Prediction of RNA secondary structure including kissing hairpin motifs
WABI'10 Proceedings of the 10th international conference on Algorithms in bioinformatics
Topology and prediction of RNA pseudoknots
Bioinformatics
RNA-RNA interaction prediction and antisense RNA target search
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
RNA folding including pseudoknots: a new parameterized algorithm and improved upper bound
WABI'07 Proceedings of the 7th international conference on Algorithms in Bioinformatics
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Predicting the folding of an RNA sequence, while allowing general pseudoknots (PK), consists in finding a minimal free-energy matching of its n positions. Assuming independently contributing base-pairs, the problem can be solved in Θ(n3)-time using a variant of the maximal weighted matching. By contrast, the problem was previously proven NP-Hard in the more realistic nearest-neighbor energy model. In this work, we consider an intermediate model, called the stacking-pairs energy model. We extend a result by Lyngsø, showing that RNA folding with PK is NP-Hard within a large class of parametrization for the model. We also show the approximability of the problem, by giving a practical Θ(n3) algorithm that achieves at least a 5-approximation for any parametrization of the stacking model. This contrasts nicely with the nearest-neighbor version of the problem, which we prove cannot be approximated within any positive ratio, unless P=NP.