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Related Concept Videos

RNA-seq03:21

RNA-seq

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 microarray-based...
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 Structure01:19

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...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Related Experiment Video

Updated: Jun 19, 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

From consensus structure prediction to RNA gene finding.

Stephan H Bernhart1, Ivo L Hofacker

  • 1Department of Theoretical Chemistry, University of Vienna, Währingerstrasse 17, A-1090 Wien, Austria. berni@tbi.univie.ac.at

Briefings in Functional Genomics & Proteomics
|October 17, 2009
PubMed
Summary
This summary is machine-generated.

Predicting RNA secondary structures improves with consensus structure analysis of related sequences. This method aids in detecting non-coding RNAs by leveraging sequence variation for better RNA structure prediction.

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RNA Secondary Structure Prediction Using High-throughput SHAPE
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Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae

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Related Experiment Videos

Last Updated: Jun 19, 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

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae
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Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae

Published on: February 27, 2026

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Accurate RNA structure prediction is crucial for bioinformatics.
  • Single RNA sequence structure prediction has limited accuracy.
  • Consensus structure prediction from related RNA sequences enhances accuracy.

Purpose of the Study:

  • To review strategies for predicting consensus secondary structures of RNA.
  • To demonstrate the utility of consensus structure prediction for identifying non-coding RNA genes.
  • To improve RNA structure prediction by exploiting sequence variation.

Main Methods:

  • Exploiting patterns of sequence (co-)variation in related RNA sequences.
  • Computing consensus secondary structures.
  • Utilizing conserved RNA structures under selective pressure.

Main Results:

  • Consensus structure prediction significantly improves RNA structure prediction accuracy.
  • Sequence variation patterns are key to enhancing structure prediction.
  • Consensus structure prediction serves as a starting point for de novo non-coding RNA detection.

Conclusions:

  • Consensus structure prediction is a powerful approach for RNA analysis.
  • This method enhances the detection of structured non-coding RNAs.
  • Leveraging sequence evolution improves RNA gene discovery.