ArticleBioinformatics (Oxford, England)2018
New algorithms to represent complex pseudoknotted RNA structures in dot-bracket notation.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed.
- Hierarchical analysis of RNA secondary structures with pseudoknots based on sections.PLoS computational biology · 2026Article
- PseudoknotVisualizer: Visualization of pseudoknots on three-dimensional RNA structures.PLoS computational biology · 2025Article
- Cryo-EM structure of ribosome from pathogenic protozoa Entamoeba histolytica reveals unique features of its architecture.Nature communications · 2025Article
- TARNAS: A Software Tool for Abstracting and Translating RNA Secondary Structures.International journal of molecular sciences · 2025Article
- RNA-Puzzles Round V: blind predictions of 23 RNA structures.Nature methods · 2025Article
- Dissecting the Conformational Heterogeneity of Stem-Loop Substructures of the Fifth Element in the 5'-Untranslated Region of SARS-CoV-2.Journal of the American Chemical Society · 2024Article
- Improving ncRNA family prediction using multi-modal contrastive learning of sequence and structure.Bioinformatics (Oxford, England) · 2024Article
- Predicting RNA sequence-structure likelihood via structure-aware deep learning.BMC bioinformatics · 2024Article
- Assessing RNA atomistic force fields via energy landscape explorations in implicit solvent.Biophysical reviews · 2024Review
- Knotify_V2.0: Deciphering RNA Secondary Structures with H-Type Pseudoknots and Hairpin Loops.Genes · 2024Article
- Automatic generation of pseudoknotted RNAs taxonomy.BMC bioinformatics · 2023Article
- Biotite: new tools for a versatile Python bioinformatics library.BMC bioinformatics · 2023Article
- Machine learning for RNA 2D structure prediction benchmarked on experimental data.Briefings in bioinformatics · 2023Review
- Predicting 3D structures and stabilities for complex RNA pseudoknots in ion solutions.Biophysical journal · 2023Article
- RNAloops: a database of RNA multiloops.Bioinformatics (Oxford, England) · 2022Article
- Computational Pipeline for Reference-Free Comparative Analysis of RNA 3D Structures Applied to SARS-CoV-2 UTR Models.International journal of molecular sciences · 2022Article
- RNAspider: a webserver to analyze entanglements in RNA 3D structures.Nucleic acids research · 2022Article
- Knotify: An Efficient Parallel Platform for RNA Pseudoknot Prediction Using Syntactic Pattern Recognition.Methods and protocols · 2022Article
- RNAlign2D: a rapid method for combined RNA structure and sequence-based alignment using a pseudo-amino acid substitution matrix.BMC bioinformatics · 2021Article
- Entanglements of structure elements revealed in RNA 3D models.Nucleic acids research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Understanding the formation, architecture and roles of pseudoknots in RNA structures are one of the most difficult challenges in RNA computational biology and structural bioinformatics. Methods predicting pseudoknots typically perform this with poor accuracy, often despite experimental data incorporation. Existing bioinformatic approaches differ in terms of pseudoknots' recognition and revealing their nature. A few ways of pseudoknot classification exist, most common ones refer to a genus or order. Following the latter one, we propose new algorithms that identify pseudoknots in RNA structure provided in BPSEQ format, determine their order and encode in dot-bracket-letter notation. The proposed encoding aims to illustrate the hierarchy of RNA folding. Results: New algorithms are based on dynamic programming and hybrid (combining exhaustive search and random walk) approaches. They evolved from elementary algorithm implemented within the workflow of RNA FRABASE 1.0, our database of RNA structure fragments. They use different scoring functions to rank dissimilar dot-bracket representations of RNA structure. Computational experiments show an advantage of new methods over the others, especially for large RNA structures. Availability and implementation: Presented algorithms have been implemented as new functionality of RNApdbee webserver and are ready to use at http://rnapdbee.cs.put.poznan.pl. Contact: mszachniuk@cs.put.poznan.pl. Supplementary information: Supplementary data are available at Bioinformatics online.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.