ArticleBioinformatics (Oxford, England)2020
LinearPartition: linear-time approximation of RNA folding partition function and base-pairing probabilities.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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43 citing papers in PubMed.
- Longer Is Not Always Better: Effects of Equilibration Length on Umbrella Sampling Estimations for RNA Hairpin Folding Stabilities.bioRxiv : the preprint server for biology · 2026Article
- Probabilistic RNA designability via interpretable ensemble approximation and dynamic decomposition.Bioinformatics (Oxford, England) · 2026Article
- Fine-scale structural information substantially improves mRNA therapeutic stability prediction.Molecular therapy. Nucleic acids · 2026Article
- LinearCapR: linear-time computation of per-nucleotide structural-context probabilities of RNA without base-pair span limits.Bioinformatics (Oxford, England) · 2026Article
- Inferring the qualities of protein-RNA models with graph transformers.Bioinformatics (Oxford, England) · 2026Article
- Metamorphosis and lncRNAs: A Close Relationship.Genesis (New York, N.Y. : 2000) · 2026Review
- SamplingDesign: RNA design via continuous optimization with coupled variables and Monte-Carlo sampling.Nature communications · 2026Article
- NTFold: Structure-Sensing Nucleotide Attention Learning for RNA Secondary Structure Prediction.Sensors (Basel, Switzerland) · 2026Article
- Modeling RNA duplex dynamics with Gibbs sampling enhances base-pair prediction accuracy and reveals structural activity profiles.NAR genomics and bioinformatics · 2025Article
- EnsembleDesign: messenger RNA design minimizing ensemble free energy via probabilistic lattice parsing.Bioinformatics (Oxford, England) · 2025Article
- Enhanced RNA secondary structure prediction through integrative deep learning and structural context analysis.Nucleic acids research · 2025Article
- Quantifying the Evolution of SNPs That Affect RNA Secondary Structure in Arabidopsis thaliana Genes.Molecular biology and evolution · 2025Article
- Comprehensive benchmarking of large language models for RNA secondary structure prediction.Briefings in bioinformatics · 2025Article
- memerna: Sparse RNA folding including coaxial stacking.Journal of molecular biology · 2025Article
- SARS-CoV-2 CoCoPUTs: analyzing GISAID and NCBI data to obtain codon statistics, mutations, and free energy over a multiyear period.Virus evolution · 2025Article
- A divide-and-conquer approach based on deep learning for long RNA secondary structure prediction: Focus on pseudoknots identification.PloS one · 2025Article
- Using the RNAstructure Software Package to Predict Conserved RNA Structures.Current protocols · 2024Article
- Predicting RNA sequence-structure likelihood via structure-aware deep learning.BMC bioinformatics · 2024Article
- LinearAlifold: Linear-time consensus structure prediction for RNA alignments.Journal of molecular biology · 2024Article
- NNDB: An Expanded Database of Nearest Neighbor Parameters for Predicting Stability of Nucleic Acid Secondary Structures.Journal of molecular biology · 2024Article
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4 authors.
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Abstract
motivationRNA secondary structure prediction is widely used to understand RNA function. Recently, there has been a shift away from the classical minimum free energy methods to partition function-based methods that account for folding ensembles and can therefore estimate structure and base pair probabilities. However, the classical partition function algorithm scales cubically with sequence length, and is therefore prohibitively slow for long sequences. This slowness is even more severe than cubic-time free energy minimization due to a substantially larger constant factor in runtime.
resultsInspired by the success of our recent LinearFold algorithm that predicts the approximate minimum free energy structure in linear time, we design a similar linear-time heuristic algorithm, LinearPartition, to approximate the partition function and base-pairing probabilities, which is shown to be orders of magnitude faster than Vienna RNAfold and CONTRAfold (e.g. 2.5 days versus 1.3 min on a sequence with length 32 753 nt). More interestingly, the resulting base-pairing probabilities are even better correlated with the ground-truth structures. LinearPartition also leads to a small accuracy improvement when used for downstream structure prediction on families with the longest length sequences (16S and 23S rRNAs), as well as a substantial improvement on long-distance base pairs (500+ nt apart). AVAILABILITY AND IMPLEMENTATION: Code: http://github.com/LinearFold/LinearPartition; Server: http://linearfold.org/partition. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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