ArticleBioinformatics (Oxford, England)2019
LinearFold: linear-time approximate RNA folding by 5'-to-3' dynamic programming and beam search.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers.
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91 citing papers in PubMed.
- Crosstalk between RNA secondary and three-dimensional structure prediction: a comprehensive study.RNA biology · 2026Article
- UFold-X: an enhanced Dual & Dynamic U-Mamba model for long-range RNA secondary structure prediction.Nucleic acids research · 2026Article
- RNARL: reinforcement learning-driven unified generative framework for multi-objective RNA codon design.Genome biology · 2026Article
- DeepExoMir: A Reproducible RNA Language Model Framework for CLIP-Seq-Supported MicroRNA Target-Site Prioritization.International journal of molecular sciences · 2026Article
- Probabilistic RNA designability via interpretable ensemble approximation and dynamic decomposition.Bioinformatics (Oxford, England) · 2026Article
- LinearCapR: linear-time computation of per-nucleotide structural-context probabilities of RNA without base-pair span limits.Bioinformatics (Oxford, England) · 2026Article
- Genomic and evolutionary factors influencing the prediction accuracy of optimal growth temperature in prokaryotes.mSystems · 2026Article
- Graph-based RNA structural representation reveals determinants of subcellular localization.Briefings in bioinformatics · 2026Article
- Structural and phylogenetic analyses of umbravirus and umbra-like virus genomes suggest evolution of capsid-like proteins from 30K movement proteins.Journal of virology · 2026Article
- Exploring Secondary Structure Predictions for RNA-Targeted Drug Discovery: Power and Challenges.Journal of chemical information and modeling · 2026Article
- Machine learning for RNA secondary structure prediction: a review of current methods and challenges.RNA (New York, N.Y.) · 2026Review
- SamplingDesign: RNA design via continuous optimization with coupled variables and Monte-Carlo sampling.Nature communications · 2026Article
- CodonRL: Multi-Objective Codon Sequence Optimization Using Demonstration-Guided Reinforcement Learning.bioRxiv : the preprint server for biology · 2026Article
- Article
- NTFold: Structure-Sensing Nucleotide Attention Learning for RNA Secondary Structure Prediction.Sensors (Basel, Switzerland) · 2026Article
- LinearCDSfold: a tool for co-optimizing secondary structure stability and codon usage in coding sequence design.Bioinformatics advances · 2026Article
- Hierarchical analysis of RNA secondary structures with pseudoknots based on sections.PLoS computational biology · 2026Article
- RNA triplet repeats: improved algorithms for structure prediction and interactions.Algorithms for molecular biology : AMB · 2025Article
- ERNIE-RNA: an RNA language model with structure-enhanced representations.Nature communications · 2025Article
- Deep generative optimization of mRNA codon sequences for enhanced mRNA translation and therapeutic efficacy.Nature communications · 2025Article
31 more citing papers are in PubMed but not listed here.
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7 authors.
Funding
Abstract
motivationPredicting the secondary structure of an ribonucleic acid (RNA) sequence is useful in many applications. Existing algorithms [based on dynamic programming] suffer from a major limitation: their runtimes scale cubically with the RNA length, and this slowness limits their use in genome-wide applications.
resultsWe present a novel alternative O(n3)-time dynamic programming algorithm for RNA folding that is amenable to heuristics that make it run in O(n) time and O(n) space, while producing a high-quality approximation to the optimal solution. Inspired by incremental parsing for context-free grammars in computational linguistics, our alternative dynamic programming algorithm scans the sequence in a left-to-right (5'-to-3') direction rather than in a bottom-up fashion, which allows us to employ the effective beam pruning heuristic. Our work, though inexact, is the first RNA folding algorithm to achieve linear runtime (and linear space) without imposing constraints on the output structure. Surprisingly, our approximate search results in even higher overall accuracy on a diverse database of sequences with known structures. More interestingly, it leads to significantly more accurate predictions on the longest sequence families in that database (16S and 23S Ribosomal RNAs), as well as improved accuracies for long-range base pairs (500+ nucleotides apart), both of which are well known to be challenging for the current models. AVAILABILITY AND IMPLEMENTATION: Our source code is available at https://github.com/LinearFold/LinearFold, and our webserver is at http://linearfold.org (sequence limit: 100 000nt). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.