ArticleMethods in molecular biology (Clifton, N.J.)2017
Predicting RNA Structure with Vfold.
Article in Methods in molecular biology (Clifton, N.J.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Comparison of Three Computational Tools for the Prediction of RNA Tertiary Structures.Non-coding RNA · 2024Article
- Machine learning in RNA structure prediction: Advances and challenges.Biophysical journal · 2024Review
- State-of-the-RNArt: benchmarking current methods for RNA 3D structure prediction.NAR genomics and bioinformatics · 2024Article
- Prediction of 3D RNA Structures from Sequence Using Energy Landscapes of RNA Dimers: Application to RNA Tetraloops.Journal of chemical theory and computation · 2024Article
- Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities.Diagnostics (Basel, Switzerland) · 2024Review
- RNA threading with secondary structure and sequence profile.Bioinformatics (Oxford, England) · 2024Article
- Accurate prediction of protein-nucleic acid complexes using RoseTTAFoldNA.Nature methods · 2024Article
- When will RNA get its AlphaFold moment?Nucleic acids research · 2023Article
- Identification and characterization of RNA pentaloop sequence families.NAR genomics and bioinformatics · 2023Article
- Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines?Nano today · 2022Article
- 3dDNA: A Computational Method of Building DNA 3D Structures.Molecules (Basel, Switzerland) · 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
- Probing RNA structures and functions by solvent accessibility: an overview from experimental and computational perspectives.Briefings in bioinformatics · 2022Review
- VfoldMCPX: predicting multistrand RNA complexes.RNA (New York, N.Y.) · 2022Article
- rsRNASP: A residue-separation-based statistical potential for RNA 3D structure evaluation.Biophysical journal · 2022Article
- Modelling aptamers with nucleic acid mimics (NAM): From sequence to three-dimensional docking.PloS one · 2022Article
- Recent Advances in Micro/Nanomaterial-Based Aptamer Selection Strategies.Molecules (Basel, Switzerland) · 2021Review
- Artificial Intelligence in Aptamer-Target Binding Prediction.International journal of molecular sciences · 2021Review
- RNA 3D Structure Prediction Using Coarse-Grained Models.Frontiers in molecular biosciences · 2021Review
- An apta-aggregation based machine learning assay for rapid quantification of lysozyme through texture parameters.PloS one · 2021Article
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Authors and funding
3 authors.
Funding
Abstract
In order to carry out biological functions, RNA molecules must fold into specific three-dimensional (3D) structures. Current experimental methods to determine RNA 3D structures are expensive and time consuming. With the recent advances in computational biology, RNA structure prediction is becoming increasingly reliable. This chapter describes a recently developed RNA structure prediction software, Vfold, a virtual bond-based RNA folding model. The main features of Vfold are the physics-based loop free energy calculations for various RNA structure motifs and a template-based assembly method for RNA 3D structure prediction. For illustration, we use the yybP-ykoY Orphan riboswitch as an example to show the implementation of the Vfold model in RNA structure prediction from the sequence.
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