Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

RNA Structure

RNA Structure

The basic structure of RNA consists of a string of ribonucleotides attached by phosphodiester bonds. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA) involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three...

RNA Stability

RNA Stability

Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...

Nucleic Acid Structure

Nucleic Acid Structure

The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA...

Leaky Scanning

Leaky Scanning

During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA. Marilyn Kozak discovered that the sequence RCCAUGG (where R...

Protein Folding Quality Check in the RER

Protein Folding Quality Check in the RER

ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...

Nucleic Acids

Nucleic Acids

Nucleic acids are the most important macromolecules for the continuity of life. They carry the cell's genetic blueprint and carry instructions for its functioning.
DNA and RNA
The two main types of nucleic acids are deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). DNA is the genetic material in all living organisms, ranging from single-celled bacteria to multicellular mammals. It is in the nucleus of eukaryotes and in the organelles, chloroplasts, and mitochondria. In prokaryotes,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

RNA structure prediction using deep learning - A comprehensive review.

Computers in biology and medicine·2025

Same author

Information sharing within a social network is key to behavioral flexibility-Lessons from mice tested under seminaturalistic conditions.

Science advances·2025

Same author

Mmp14 is required for matrisome homeostasis and circadian rhythm in fibroblasts.

Matrix biology : journal of the International Society for Matrix Biology·2023

Same author

Quantified density of performance-degrading near-interface traps in SiC MOSFETs.

Scientific reports·2022

Same author

On training targets for deep learning approaches to clean speech magnitude spectrum estimation.

The Journal of the Acoustical Society of America·2021

Same author

An objective measure of quality for time-scale modification of audio.

The Journal of the Acoustical Society of America·2021

Search research articles

Related Experiment Video

Updated: May 15, 2025

RNA Secondary Structure Prediction Using High-throughput SHAPE

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Transformers in RNA structure prediction: A review.

Mayank Chaturvedi¹, Mahmood A Rashid¹, Kuldip K Paliwal¹

¹Signal Processing Laboratory, School of Engineering and Built Environment, Griffith University, Brisbane, QLD, 4111, Australia.

Computational and Structural Biotechnology Journal

|April 11, 2025

Summary

This summary is machine-generated.

Transformer models, using self-attention, are advancing RNA structure prediction. This review details these deep learning networks, their innovations, and future directions in predicting RNA secondary and tertiary structures.

Keywords:

Deep learning RNA structure prediction Self-attention Transformers

More Related Videos

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Published on: December 9, 2022

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

Published on: May 24, 2017

Related Experiment Videos

Last Updated: May 15, 2025

RNA Secondary Structure Prediction Using High-throughput SHAPE

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Published on: December 9, 2022

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

Published on: May 24, 2017

Area of Science:

Computational Biology
Bioinformatics
Machine Learning

Background:

The Transformer architecture, initially for natural language processing, excels at sequential data.
RNA's nucleotide sequence forms its structure, making it suitable for Transformer application.
Deep learning models like Transformers are increasingly used for RNA structure prediction.

Purpose of the Study:

To review Transformer-based models for RNA structure prediction.
To analyze architectural innovations and performance improvements.
To identify current limitations and future research avenues.

Main Methods:

Review of existing literature on Transformer applications in RNA structure prediction.
In-depth analysis of Transformer model architectures.
Comparative assessment of Transformer performance against other deep learning methods.

Main Results:

Transformer models demonstrate competitive or superior performance in RNA structure prediction.
Architectural innovations in Transformers contribute to enhanced prediction accuracy.
Identified areas for improvement and future development in Transformer-based RNA prediction.

Conclusions:

Transformer models represent a significant advancement in RNA structure prediction.
Continued evolution of Transformer techniques is expected to yield further breakthroughs.
This review provides a comprehensive overview and roadmap for future research.