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

Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. 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): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...

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...

You might also read

Related Articles

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

Sort by

Same author

What will be the future of computational biology for macromolecules in the era of AI?

PLoS computational biology·2026

Same author

The versatility of the CHASE domain in one-component systems of c-di-GMP signal transduction from <i>P. aeruginosa</i>.

Journal of bacteriology·2026

Same author

Mass spectrometry integrates protein design into structural biology method development.

QRB discovery·2026

Same author

The Emerging Role of Explainable Artificial Intelligence in EEG-Based Autism Research: A Systematic Review.

NeuroSci·2026

Same author

m<sup>6</sup>A RNA methylation modulates Zika virus infection by regulating serine proteases in <i>Aedes albopictus</i>.

bioRxiv : the preprint server for biology·2026

Same author

Smart Microfluidics: A curated dataset of microfluidic liposome formulations with cross-laboratory validation for machine-learning applications.

Data in brief·2026

Search research articles

Related Experiment Video

Updated: Feb 21, 2026

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Published on: September 28, 2017

A deep learning framework for comprehensive prediction of human RNA G-quadruplex-binding proteins.

Serena Rosignoli¹, Sophie Taraglio², Francesco Di Luzio³

¹Centre for Regenerative Medicine "Stefano Ferrari", Department of Life Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy.

Bioinformatics (Oxford, England)

|February 19, 2026

Summary

We developed a deep learning model to predict RNA G-quadruplex-binding proteins (RG4BPs), crucial for RNA metabolism and stress. This tool identified thousands of new RG4BP candidates, advancing RNA regulation research.

More Related Videos

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

Published on: February 17, 2023

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

Related Experiment Videos

Last Updated: Feb 21, 2026

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Published on: September 28, 2017

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

Published on: February 17, 2023

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

Area of Science:

Computational Biology
Molecular Biology
Bioinformatics

Background:

G-quadruplex-binding proteins (G4BPs) are vital for RNA metabolism and cellular stress responses.
Experimental identification of G4BPs is challenging, necessitating computational approaches.

Purpose of the Study:

To develop and validate a deep learning framework for predicting RNA G4BPs (RG4BPs).
To identify novel RG4BP candidates within the human proteome.
To provide a user-friendly web server for RG4BP prediction and analysis.

Main Methods:

Integration of diverse encoding strategies and neural architectures, including ESM-2 protein language model embeddings and an LSTM architecture.
Application of the trained model to the human proteome for candidate identification.
Development of the G4REP web server for accessible RG4BP prediction.

Main Results:

The best-performing deep learning model achieved 86% accuracy in identifying RG4BPs.
Identified 2,160 high-confidence RG4BP candidates in the human proteome.
Discovered that many RG4BP candidates possess intrinsically disordered regions and are enriched in stress granules, suggesting a link to cellular stress.

Conclusions:

The study provides an effective computational approach to explore the landscape of RG4BPs.
Novel RG4BP candidates and their potential roles in RNA regulation and stress response pathways were uncovered.
The G4REP web server facilitates broad access to RG4BP prediction and analysis tools.