Simple fast algorithms for the editing distance between trees and related problems
SIAM Journal on Computing
Finding Common Sequence and Structure Motifs in a Set of RNA Sequences
Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology
Designing RNA structures: natural and artificial selection
Proceedings of the sixth annual international conference on Computational biology
Strand design for biomolecular computation
Theoretical Computer Science - Natural computing
Classifying RNA pseudoknotted structures
Theoretical Computer Science
Fast detection of common sequence structure patterns in RNAs
Journal of Discrete Algorithms
Lifting Prediction to Alignment of RNA Pseudoknots
RECOMB 2'09 Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology
RNA pseudoknot prediction via an evolutionary algorithm
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Sparsification of RNA structure prediction including pseudoknots
WABI'10 Proceedings of the 10th international conference on Algorithms in bioinformatics
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Algorithms for pseudoknot classification
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Lynx: a programmatic SAT solver for the RNA-folding problem
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
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RNA molecules are sequences of nucleotides that serve as more than mere intermediaries between DNA and proteins, e.g. as catalytic molecules. Computational prediction of RNA secondary structure is among the few structure prediction problems that can be solved satisfactory in polynomial time. Most work has been done to predict structures that do not contain pseudoknots. Allowing pseudoknots introduce modelling and computational problems. In this paper we consider the problem of predicting RNA secondary structure when certain types of pseudoknots are allowed. We first present an algorithm that in time &Ogr;(n5) and space &Ogr;(n3) predicts the secondary structure of an RNA sequence of length n in a model that allows certain kinds of pseudoknots. We then prove that the general problem of predicting RNA secondary structure containing pseudoknots is NP-complete for a large class of reasonable models of pseudoknots.