ArticleBMC bioinformatics2014
A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Spark: sparse hierarchical energy minimization for scalable prediction of RNA pseudoknots.Bioinformatics (Oxford, England) · 2026Article
- AI-powered mapping of tumor immunity for optimized mRNA vaccine engineering.Frontiers in oncology · 2026Review
- Assessment of Nucleic Acid Structure Prediction in CASP16.Proteins · 2026Article
- Assessment of nucleic acid structure prediction in CASP16.bioRxiv : the preprint server for biology · 2025Article
- CParty: hierarchically constrained partition function of RNA pseudoknots.Bioinformatics (Oxford, England) · 2024Article
- Ribonanza: deep learning of RNA structure through dual crowdsourcing.bioRxiv : the preprint server for biology · 2024Article
- DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning.Journal of chemical information and modeling · 2024Article
- SparseRNAfolD: optimized sparse RNA pseudoknot-free folding with dangle consideration.Algorithms for molecular biology : AMB · 2024Article
- Computational biology and artificial intelligence in mRNA vaccine design for cancer immunotherapy.Frontiers in cellular and infection microbiology · 2024Review
- Discovery of RNA secondary structural motifs using sequence-ordered thermodynamic stability and comparative sequence analysis.MethodsX · 2023Article
- Automated design of dynamic programming schemes for RNA folding with pseudoknots.Algorithms for molecular biology : AMB · 2023Article
- Shapify: Paths to SARS-CoV-2 frameshifting pseudoknot.PLoS computational biology · 2023Article
- Exploring the landscape of tools and resources for the analysis of long non-coding RNAs.Computational and structural biotechnology journal · 2023Review
- KnotAli: informed energy minimization through the use of evolutionary information.BMC bioinformatics · 2022Article
- Knotify: An Efficient Parallel Platform for RNA Pseudoknot Prediction Using Syntactic Pattern Recognition.Methods and protocols · 2022Article
- SSRTool: A web tool for evaluating RNA secondary structure predictions based on species-specific functional interpretability.Computational and structural biotechnology journal · 2022Article
- Progress toward SHAPE Constrained Computational Prediction of Tertiary Interactions in RNA Structure.Non-coding RNA · 2021Article
- Research on RNA secondary structure predicting via bidirectional recurrent neural network.BMC bioinformatics · 2021Article
- A combinatorial method to isolate short ribozymes from complex ribozyme libraries.Nucleic acids research · 2020Article
- An efficient simulated annealing algorithm for the RNA secondary structure prediction with Pseudoknots.BMC genomics · 2019Article
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Abstract
backgroundImproving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information.
resultsWe present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0.Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure.Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets.
conclusionsIterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in this work are freely available at http://www.cs.ubc.ca/~hjabbari/software.php.
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