Pair Stochastic Tree Adjoining Grammars for Aligning and Predicting Pseudoknot RNA Structures
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
Prediction of Consensus RNA Secondary Structures Including Pseudoknots
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
RnaPredict—An Evolutionary Algorithm for RNA Secondary Structure Prediction
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Approximation scheme for RNA structure prediction based on base pair stacking
SMO'07 Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization
Memory efficient alignment between RNA sequences and stochastic grammar models of pseudoknots
International Journal of Bioinformatics Research and Applications
A rule-based approach for RNA pseudoknot prediction
International Journal of Data Mining and Bioinformatics
Improved Approximation Algorithms for Predicting RNA Secondary Structures with Arbitrary Pseudoknots
AAIM '07 Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management
A Seed-Based Method for Predicting Common Secondary Structures in Unaligned RNA Sequences
MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
RNA Pseudoknot Folding through Inference and Identification Using TAGRNA
BICoB '09 Proceedings of the 1st International Conference on Bioinformatics and Computational Biology
Software note: An RNA folding algorithm including pseudoknots based on dynamic weighted matching
Computational Biology and Chemistry
Approximation algorithm and scheme for RNA structure prediction
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Delta: a toolset for the structural analysis of biological sequences on a 3D triangular lattice
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
K-partite RNA secondary structures
WABI'09 Proceedings of the 9th international conference on Algorithms in bioinformatics
Mining characteristic relations bind to RNA secondary structures
IEEE Transactions on Information Technology in Biomedicine
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Function Annotation for Pseudoknot Using Structure Similarity
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Rapid ab initio RNA folding including pseudoknots via graph tree decomposition
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
A new pseudoknots folding algorithm for RNA structure prediction
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
Profiling and searching for RNA pseudoknot structures in genomes
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
Profiling and searching for RNA pseudoknot structures in genomes
Transactions on Computational Systems Biology II
RNA folding including pseudoknots: a new parameterized algorithm and improved upper bound
WABI'07 Proceedings of the 7th international conference on Algorithms in Bioinformatics
Constructing structural alignment of RNA sequences by detecting and assessing conserved stems
LSMS'07 Proceedings of the 2007 international conference on Life System Modeling and Simulation
ChainKnot: a comparative H-type pseudoknot prediction tool using multiple ab initio folding tools
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
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Motivation: Pseudoknots have generally been excluded from the prediction of RNA secondary structures due to its difficulty in modeling. Although, several dynamic programming algorithms exist for the prediction of pseudoknots using thermodynamic approaches, they are neither reliable nor efficient. On the other hand, comparative methods are more reliable, but are often done in an ad hoc manner and require expert intervention. Maximum weighted matching, an algorithm for pseudoknot prediction with comparative analysis, suffers from low-prediction accuracy in many cases. Results: Here we present an algorithm, iterated loop matching, for reliably and efficiently predicting RNA secondary structures including pseudoknots. The method can utilize either thermodynamic or comparative information or both, thus is able to predict pseudoknots for both aligned and individual sequences. We have tested the algorithm on a number of RNA families. Using 8--12 homologous sequences, the algorithm correctly identifies more than 90% of base-pairs for short sequences and 80% overall. It correctly predicts nearly all pseudoknots and produces very few spurious base-pairs for sequences without pseudoknots. Comparisons show that our algorithm is both more sensitive and more specific than the maximum weighted matching method. In addition, our algorithm has high-prediction accuracy on individual sequences, comparable with the PKNOTS algorithm, while using much less computational resources. Availability: The program has been implemented in ANSI C and is freely available for academic use at http://www.cse.wustl.edu/~zhang/projects/rna/ilm/ Supplementary information: http://www.cse.wustl.edu/~zhang/projects/rna/ilm/