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Related Concept Videos

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...
Protein Folding Quality Check in the RER01:29

Protein Folding Quality Check in the RER

ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
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...
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: May 11, 2026

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

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Quantifying variances in comparative RNA secondary structure prediction.

James W J Anderson1, Ádám Novák, Zsuzsanna Sükösd

  • 1Department of Statistics, South Parks Road, Oxford, UK. anderson@stats.ox.ac.uk

BMC Bioinformatics
|May 3, 2013
PubMed
Summary

Researchers identified factors causing inaccurate RNA secondary structure predictions, improving accuracy and quantifying prediction uncertainty. This work enhances understanding of RNA structure modeling and its limitations.

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Last Updated: May 11, 2026

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

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Published on: May 31, 2013

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

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Advancements in sequencing and transcriptomics reveal regulatory roles of RNA structural changes.
  • RNA secondary structure prediction is crucial but suffers from high predictive accuracy variance.
  • Reasons for prediction accuracy variances remain poorly quantified.

Purpose of the Study:

  • To explore factors contributing to poor RNA secondary structure prediction quality.
  • To establish a quantified relationship between alignment quality and prediction accuracy.
  • To develop new measures for quantifying uncertainty in RNA structure predictions.

Main Methods:

  • Exploration of factors influencing RNA secondary structure prediction.
  • Quantification of the relationship between alignment quality and prediction accuracy.
  • Definition of two novel measures for quantifying uncertainty in alignment-based structure predictions.

Main Results:

  • Established a quantified relationship between alignment quality and prediction accuracy.
  • Introduced two new measures for quantifying uncertainty, improving on existing scores like PPfold's reliability score.
  • Characterized several reasons for prediction variances, including alignment uncertainty and base-pair probabilities.

Conclusions:

  • The developed measures improve upon existing RNA secondary structure prediction reliability scores.
  • Many sources of prediction variance were successfully identified and characterized.
  • Unaccounted variability suggests limitations within the RNA secondary structure predictive models themselves.