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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: May 11, 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

Structural RNA alignment by multi-objective optimization.

Thomas Schnattinger1, Uwe Schöning, Hans A Kestler

  • 1Institute of Theoretical Computer Science, Ulm University, 89069 Ulm, Germany.

Bioinformatics (Oxford, England)
|April 27, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a novel multi-objective dynamic programming algorithm for RNA sequence-structure alignment. It efficiently calculates Pareto-optimal alignments, offering a comprehensive view of trade-offs without arbitrary weighting.

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Related Experiment Videos

Last Updated: May 11, 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

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

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Accurate RNA sequence-structure alignment remains a significant challenge in bioinformatics.
  • Current methods often rely on subjective weighting of sequence and structure components.
  • Incorporating secondary structure into alignment optimization is crucial for understanding RNA function.

Purpose of the Study:

  • To develop a method for calculating RNA sequence-structure alignments that avoids arbitrary weighting.
  • To present a set of Pareto-optimal alignments representing all possible trade-offs between sequence and structure.
  • To address the open problem of reliable RNA alignment by utilizing multi-objective optimization.

Main Methods:

  • A practical multi-objective dynamic programming algorithm was developed.
  • The algorithm calculates the set of Pareto-optimal solutions for pairwise RNA sequence-structure alignment.
  • The implementation is available as open-source software.

Main Results:

  • The study presents a novel algorithm for computing Pareto-optimal RNA sequence-structure alignments.
  • Demonstrated the utility and advantages of the multi-objective approach over single-objective methods.
  • Provided a set of alignments that capture all possible trade-offs between sequence and structure.

Conclusions:

  • Multi-objective optimization offers a robust framework for RNA sequence-structure alignment.
  • The developed algorithm provides a more comprehensive and objective approach compared to traditional methods.
  • This method advances the field of RNA structural bioinformatics by offering a better solution to alignment challenges.