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Related Concept Videos

RNA Structure01:19

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 Structure01:23

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 Structure01:23

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...
Nucleic Acid Structure01:25

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 has a double-helix structure. The...

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Related Experiment Video

Updated: Jun 4, 2026

Monitoring Equilibrium Changes in RNA Structure by 'Peroxidative' and 'Oxidative' Hydroxyl Radical Footprinting
13:41

Monitoring Equilibrium Changes in RNA Structure by 'Peroxidative' and 'Oxidative' Hydroxyl Radical Footprinting

Published on: October 17, 2011

Constructing accurate contact maps for hydroxyl-radical-cleavage-based high-throughput RNA structure inference.

Jinkyu Kim1, Hanjoo Kim, Hyeyoung Min

  • 1School of Electrical Engineering,Korea University, Seoul 136-713, Korea. supmace@korea.ac.kr

IEEE Transactions on Bio-Medical Engineering
|February 5, 2011
PubMed
Summary

This study introduces a computational method to automatically identify RNA residue interactions from gel electrophoresis data. This innovation significantly improves the speed and accuracy of RNA tertiary structure prediction.

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RNA Secondary Structure Prediction Using High-throughput SHAPE
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RNA Secondary Structure Prediction Using High-throughput SHAPE

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Related Experiment Videos

Last Updated: Jun 4, 2026

Monitoring Equilibrium Changes in RNA Structure by 'Peroxidative' and 'Oxidative' Hydroxyl Radical Footprinting
13:41

Monitoring Equilibrium Changes in RNA Structure by 'Peroxidative' and 'Oxidative' Hydroxyl Radical Footprinting

Published on: October 17, 2011

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

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

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Area of Science:

  • Biochemistry
  • Computational Biology
  • Structural Biology

Background:

  • Ribonucleic acid (RNA) tertiary structure prediction is crucial for understanding biological function.
  • Hydroxyl radical cleavage methods offer high-throughput RNA structure analysis.
  • Manual identification of residue-residue interactions from cleavage data is a significant bottleneck.

Purpose of the Study:

  • To develop an automated computational method for identifying residue-residue interaction points from 2-D electrophoresis profiles.
  • To overcome the limitations of manual analysis in RNA structure prediction workflows.

Main Methods:

  • A novel computational approach combining deconvolution for signal detection and statistical learning for noise filtering.
  • Application of the method to over 2000 actual gel profiles for validation.

Main Results:

  • The proposed technique significantly enhances specificity and sensitivity in identifying interaction points.
  • Performance improvement ranged from 56.44% to 90.50% compared to traditional methods, as measured by the F-measure for reproducing manual contact maps.

Conclusions:

  • The developed computational method effectively automates the identification of RNA residue-residue interactions.
  • This advancement is expected to substantially accelerate RNA tertiary structure inference, enabling broader exploration of RNA structures.