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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...
RNA Stability01:53

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...
RNA Stability01:53

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...

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Related Experiment Video

Updated: Jun 8, 2026

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

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Shapes of RNA pseudoknot structures.

Christian M Reidys1, Rita R Wang

  • 1Center for Combinatorics, LPMC-TJKLC, Nankai University, Tianjin, PR China. duck@santafe.edu

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|September 28, 2010
PubMed
Summary

This study introduces novel lv1k- and lv5k-shapes for RNA pseudoknot structures, generalizing existing RNA secondary structure models. We derive generating functions and asymptotic expressions for these shapes, advancing the computational analysis of RNA folding.

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Sequence-specific and Selective Recognition of Double-stranded RNAs over Single-stranded RNAs by Chemically Modified Peptide Nucleic Acids
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Sequence-specific and Selective Recognition of Double-stranded RNAs over Single-stranded RNAs by Chemically Modified Peptide Nucleic Acids

Published on: September 21, 2017

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Last Updated: Jun 8, 2026

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

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Sequence-specific and Selective Recognition of Double-stranded RNAs over Single-stranded RNAs by Chemically Modified Peptide Nucleic Acids
09:04

Sequence-specific and Selective Recognition of Double-stranded RNAs over Single-stranded RNAs by Chemically Modified Peptide Nucleic Acids

Published on: September 21, 2017

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Structural Biology

Background:

  • RNA pseudoknots are crucial for RNA function but are complex to model.
  • Existing models for RNA secondary structures (e.g., π-shapes) have limitations.
  • Generalizing these models is necessary for a comprehensive understanding of RNA structures.

Purpose of the Study:

  • To introduce and define novel abstract shapes, lv1k- and lv5k-shapes, for k-noncrossing, σ-canonical RNA pseudoknot structures.
  • To generalize existing abstract shape concepts (π'- and π-shapes) to RNA pseudoknots.
  • To develop a computational framework for analyzing these generalized shapes.

Main Methods:

  • Development of a novel approach to compute generating functions for RNA pseudoknot shapes.
  • Calculation of generating functions for lv1k- and lv5k-shapes for fixed n.
  • Application of singularity analysis to the derived generating functions.

Main Results:

  • Successful computation of generating functions for lv1k- and lv5k-shapes.
  • Derivation of explicit asymptotic expressions for these shapes using singularity analysis.
  • Demonstration of a generalized framework for analyzing complex RNA structures.

Conclusions:

  • The novel lv1k- and lv5k-shapes provide a powerful tool for studying RNA pseudoknots.
  • The derived generating functions and asymptotic expressions enable quantitative predictions of RNA structure distributions.
  • This work advances the field of RNA structure prediction and computational biology.