Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

RNA-seq03:21

RNA-seq

11.8K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
11.8K
RNA Structure01:23

RNA Structure

78.8K
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...
78.8K
RNA Structure01:19

RNA Structure

7.1K
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...
7.1K

You might also read

Related Articles

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

Sort by
Same author

DivideFold+: an AI-based tool for RNA secondary structure prediction with subdomains identification and visualization and data augmentation.

Journal of molecular biology·2026
Same author

RNAdvisor 2: A unified platform for RNA 3D model quality assessment using metrics, scoring functions, and meta-metrics.

Scientific reports·2025
Same author

A divide-and-conquer approach based on deep learning for long RNA secondary structure prediction: Focus on pseudoknots identification.

PloS one·2025
Same author

MMnc: multi-modal interpretable representation for non-coding RNA classification and class annotation.

Bioinformatics (Oxford, England)·2025
Same author

Has AlphaFold3 achieved success for RNA?

Acta crystallographica. Section D, Structural biology·2025
Same author

RNA-TorsionBERT: leveraging language models for RNA 3D torsion angles prediction.

Bioinformatics (Oxford, England)·2025
Same journal

From Pixels to Patterns: A Multidimensional Framework to Decode Cytoskeletal Organization.

Computational and structural biotechnology journal·2026
Same journal

A Large Concept Model for Mechanistic Simulation of Disease Trajectories: A Hypothesis-Generating Exemplar for Pediatric Acute Lymphoblastic Leukemia.

Computational and structural biotechnology journal·2026
Same journal

Adversarial Sequence Mutations in AlphaFold and ESMFold Reveal Nonphysical Structural Invariance, Confidence Failures, and Concerns for Protein Design.

Computational and structural biotechnology journal·2026
Same journal

High-Throughput Prediction of Protein-Protein Interactions Uncovers Hidden Molecular Networks in Biosynthetic Gene Clusters.

Computational and structural biotechnology journal·2026
Same journal

A Region-Aware Structured Framework Improves Prediction of Gene Expression from DNA Methylation.

Computational and structural biotechnology journal·2026
Same journal

Ensemble Machine Learning Approaches Predict Survival in Lower-Grade Glioma Based on Glycosphingolipid Gene Expression and Metabolic Modeling.

Computational and structural biotechnology journal·2026
See all related articles

Related Experiment Video

Updated: Jan 18, 2026

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
10:34

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

Published on: December 9, 2022

5.1K

Semi-supervised segmentation of RNA 3D structures using density-based clustering.

Quoc Khang Le1, Eric Angel1, Fariza Tahi1

  • 1Université Evry Paris-Saclay, IBISC, Evry-Courcouronnes 91020, France.

Computational and Structural Biotechnology Journal
|January 16, 2026
PubMed
Summary
This summary is machine-generated.

Researchers developed RNA3DClust, a new method to divide RNA three-dimensional (3D) structures into functional domains. This approach aids in understanding RNA

Keywords:
3D domainsLncRNAsRNA conformationSemi-supervised segmentation

More Related Videos

RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

32.2K
Analyzing and Building Nucleic Acid Structures with 3DNA
16:24

Analyzing and Building Nucleic Acid Structures with 3DNA

Published on: April 26, 2013

21.2K

Related Experiment Videos

Last Updated: Jan 18, 2026

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
10:34

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

Published on: December 9, 2022

5.1K
RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

32.2K
Analyzing and Building Nucleic Acid Structures with 3DNA
16:24

Analyzing and Building Nucleic Acid Structures with 3DNA

Published on: April 26, 2013

21.2K

Area of Science:

  • * Structural Biology
  • * Computational Biology
  • * Bioinformatics

Background:

  • * RNA molecules exhibit biological activity influenced by their spatial conformation, similar to proteins.
  • * Protein three-dimensional (3D) structures are often analyzed by dividing them into geometrically defined
  • 3D domains
  • which are compact and spatially separate regions.
  • * A comparable concept for RNA 3D structure partitioning was previously lacking.

Purpose of the Study:

  • * To introduce RNA3DClust, an algorithm for partitioning RNA 3D structures into distinct domains.
  • * To develop a method for analyzing the spatial conformation of RNA macromolecules.
  • * To provide a tool for investigating RNA function, folding, and evolution through domain analysis.

Main Methods:

  • * Application of the Mean Shift clustering algorithm to the RNA 3D structure partitioning problem.
  • * Development of a specialized post-clustering procedure to address RNA-specific domain delimitation challenges.
  • * Creation of reference datasets for RNA 3D domain annotations and a novel scoring function (Chain Segment Distance - CSD) for quality assessment.

Main Results:

  • * RNA3DClust successfully partitions RNA 3D structures into domains.
  • * Domain decompositions generated by RNA3DClust align with biological function and evolutionary analyses.
  • * A new reference dataset for long non-coding RNA (lncRNA) predicted conformations was generated.

Conclusions:

  • * RNA3DClust offers a novel computational approach for segmenting RNA 3D structures into domains.
  • * The method's domain delineations are consistent with biological and evolutionary data.
  • * RNA3DClust shows potential for analyzing the 3D structures of lncRNAs and other complex RNA molecules.