ArticlePLoS computational biology2017
Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Modeling RNA duplex dynamics with Gibbs sampling enhances base-pair prediction accuracy and reveals structural activity profiles.NAR genomics and bioinformatics · 2025Article
- Enhanced RNA secondary structure prediction through integrative deep learning and structural context analysis.Nucleic acids research · 2025Article
- In silico methods for predicting functional synonymous variants.Genome biology · 2023Review
- RNA secondary structure packages evaluated and improved by high-throughput experiments.Nature methods · 2022Article
- LTPConstraint: a transfer learning based end-to-end method for RNA secondary structure prediction.BMC bioinformatics · 2022Article
- Progress toward SHAPE Constrained Computational Prediction of Tertiary Interactions in RNA Structure.Non-coding RNA · 2021Article
- Review of machine learning methods for RNA secondary structure prediction.PLoS computational biology · 2021Review
- RNAStat: An Integrated Tool for Statistical Analysis of RNA 3D Structures.Frontiers in bioinformatics · 2021Article
- RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning.Nature communications · 2019Article
- How to benchmark RNA secondary structure prediction accuracy.Methods (San Diego, Calif.) · 2019Review
- RNAvista: a webserver to assess RNA secondary structures with non-canonical base pairs.Bioinformatics (Oxford, England) · 2019Article
- Identification of new high affinity targets for Roquin based on structural conservation.Nucleic acids research · 2018Article
- Accelerated RNA secondary structure design using preselected sequences for helices and loops.RNA (New York, N.Y.) · 2018Article
- High-throughput determination of RNA structures.Nature reviews. Genetics · 2018Review
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2 authors.
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Abstract
Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.
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