Evidence map›Paper›PMID 24884954›Full record

ArticleBMC bioinformatics2014

A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures.

Hosna Jabbari, Anne Condon

Abstract read
In one paragraph

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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23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

  1. Article
  2. Review
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  4. Assessment of nucleic acid structure prediction in CASP16.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
  6. Ribonanza: deep learning of RNA structure through dual crowdsourcing.bioRxiv : the preprint server for biology · 2024
    Article
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  9. Review
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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Hosna JabbariDepartment of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, Canada. hjabbari@cs.ubc.ca.
Anne Condon

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AlgorithmsNucleic Acid ConformationBase SequenceHigh-Throughput Nucleotide SequencingHumansRNASequence Analysis, RNASoftwareTime FactorsRNA

Identifiers

PMID24884954
PMCPMC4064103

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.