ArticleBiophysical journal2024
Predicting 3D RNA structure from the nucleotide sequence using Euclidean neural networks.
Article in Biophysical journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 18 citations in OpenAlex.
- Crosstalk between RNA secondary and three-dimensional structure prediction: a comprehensive study.RNA biology · 2026Article
- gCoSRNA: Generalizable Coaxial Stacking Prediction for RNA Junctions Using Secondary Structure.Biomolecules · 2026Article
- Article
- RNA-Puzzles Round V: blind predictions of 23 RNA structures.Nature methods · 2025Article
- Autonomous Nucleic Acid and Protein Nanocomputing Agents Engineered to Operate in Living Cells.ACS nano · 2025Review
- mRNA vaccine sequence and structure design and optimization: Advances and challenges.The Journal of biological chemistry · 2025Review
- Transformers in RNA structure prediction: A review.Computational and structural biotechnology journal · 2025Review
- Advances and Challenges in Scoring Functions for RNA-Protein Complex Structure Prediction.Biomolecules · 2024Review
- Machine learning tools advance biophysics.Biophysical journal · 2024Article
- Machine learning in RNA structure prediction: Advances and challenges.Biophysical journal · 2024Review
- Universal cold RNA phase transitions.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions.Nucleic acids research · 2024Article
- State-of-the-RNArt: benchmarking current methods for RNA 3D structure prediction.NAR genomics and bioinformatics · 2024Article
- smFRET-assisted RNA structure prediction.Communications in information and systems · 2024Article
- RNA 3D Structure Prediction: Progress and Perspective.Molecules (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Fast and accurate 3D RNA structure prediction remains a major challenge in structural biology, mostly due to the size and flexibility of RNA molecules, as well as the lack of diverse experimentally determined structures of RNA molecules. Unlike DNA structure, RNA structure is far less constrained by basepair hydrogen bonding, resulting in an explosion of potential stable states. Here, we propose a convolutional neural network that predicts all pairwise distances between residues in an RNA, using a recently described smooth parametrization of Euclidean distance matrices. We achieve high-accuracy predictions on RNAs up to 100 nt in length in fractions of a second, a factor of 10
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Registered trials
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