ArticleCommunications biology2024
Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials.
Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Article
- The RNA structural code: orchestrating gene expression and enabling precision therapies.Acta pharmacologica Sinica · 2026Review
- Genomic Characterization of a Novel Victorivirus Detected in a Sample Derived From a Human-Biting Tick in Japan.Microbiology and immunology · 2026Article
- ShapeRNA: an integrated web server for RNA secondary structure, ensemble, and functional analysis.Nucleic acids research · 2026Article
- PlanarFold: a coarse-grained molecular dynamics model of RNA in two-dimensional space.Nature communications · 2026Article
- Exploring Secondary Structure Predictions for RNA-Targeted Drug Discovery: Power and Challenges.Journal of chemical information and modeling · 2026Article
- What does it take to learn the rules of RNA base pairing? A lot less than you may think.Communications biology · 2026Article
- Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning.Briefings in bioinformatics · 2026Article
- Synthetic short RNA in cancer.Frontiers in oncology · 2026Review
- Hierarchical analysis of RNA secondary structures with pseudoknots based on sections.PLoS computational biology · 2026Article
- TVAE-RNA: ensemble-based RNA secondary structure prediction via transformer variational autoencoders.Bioinformatics (Oxford, England) · 2025Article
- Enhanced Generalizability of RNA Secondary Structure Prediction via Convolutional Block Attention Network and Ensemble Learning.Molecules (Basel, Switzerland) · 2025Article
- Aptamer Sequence Optimization and Its Application in Food Safety Analysis.Foods (Basel, Switzerland) · 2025Review
- RegRNA 3.0: expanding regulatory RNA analysis with new features for motif, interaction, and annotation.Nucleic acids research · 2025Article
- Deep generalizable prediction of RNA secondary structure via base pair motif energy.Nature communications · 2025Article
- Transformers in RNA structure prediction: A review.Computational and structural biotechnology journal · 2025Review
- A divide-and-conquer approach based on deep learning for long RNA secondary structure prediction: Focus on pseudoknots identification.PloS one · 2025Article
- Potential Transcriptional Enhancers in Coronaviruses: From Infectious Bronchitis Virus to SARS-CoV-2.International journal of molecular sciences · 2024Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Pseudoknots are key structure motifs of RNA and pseudoknotted RNAs play important roles in a variety of biological processes. Here, we present KnotFold, an accurate approach to the prediction of RNA secondary structure including pseudoknots. The key elements of KnotFold include a learned potential function and a minimum-cost flow algorithm to find the secondary structure with the lowest potential. KnotFold learns the potential from the RNAs with known structures using an attention-based neural network, thus avoiding the inaccuracy of hand-crafted energy functions. The specially designed minimum-cost flow algorithm used by KnotFold considers all possible combinations of base pairs and selects from them the optimal combination. The algorithm breaks the restriction of nested base pairs required by the widely used dynamic programming algorithms, thus enabling the identification of pseudoknots. Using 1,009 pseudoknotted RNAs as representatives, we demonstrate the successful application of KnotFold in predicting RNA secondary structures including pseudoknots with accuracy higher than the state-of-the-art approaches. We anticipate that KnotFold, with its superior accuracy, will greatly facilitate the understanding of RNA structures and functionalities.
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