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Related Concept Videos

RNA Interference01:23

RNA Interference

RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...
Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...
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...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Noncovalent Attractions in Biomolecules02:35

Noncovalent Attractions in Biomolecules

Noncovalent attractions are associations within and between molecules that influence the shape and structural stability of complexes. These interactions differ from covalent bonding in that they do not involve sharing of electrons.
Four types of noncovalent interactions are hydrogen bonds, van der Waals forces, ionic bonds, and hydrophobic interactions.
Hydrogen bonding results from the electrostatic attraction of a hydrogen atom covalently bonded to a strong-electronegative atom like oxygen,...

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Related Experiment Video

Updated: May 19, 2026

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Published on: December 9, 2022

RIsearch: fast RNA-RNA interaction search using a simplified nearest-neighbor energy model.

Anne Wenzel1, Erdinç Akbasli, Jan Gorodkin

  • 1Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg, Denmark.

Bioinformatics (Oxford, England)
|August 28, 2012
PubMed
Summary

RIsearch is a new tool that quickly and accurately predicts RNA-RNA duplexes. It speeds up genome-wide screens by filtering potential binding sites, improving efficiency for regulatory RNA research.

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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

Related Experiment Videos

Last Updated: May 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

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Regulatory non-coding RNAs interact via duplex formation.
  • Predicting RNA-RNA duplexes genome-wide is crucial but computationally intensive.
  • Existing methods balance speed and accuracy, necessitating faster pre-filtering approaches.

Purpose of the Study:

  • To develop a fast and accurate computational method for predicting RNA-RNA duplexes.
  • To create a pre-filtering tool for genome-wide RNA interaction screens.

Main Methods:

  • Implemented RIsearch using a simplified Turner energy model for rapid hybridization computation.
  • Employed a Smith-Waterman-like algorithm with a dinucleotide scoring matrix approximating Turner nearest-neighbor energies.
  • Evaluated RIsearch's speed and accuracy against existing tools like RNAplex.

Main Results:

  • RIsearch offers a significant runtime reduction (at least 2.4x faster than RNAplex) with comparable accuracy for near-complementary duplexes.
  • Demonstrated RIsearch's effectiveness in reducing candidate binding sites by up to 70% in genome-wide screens.
  • Validated performance on bacterial small RNA-messenger RNA and eukaryotic microRNA-messenger RNA interaction datasets.

Conclusions:

  • RIsearch provides a computationally efficient solution for predicting RNA-RNA interactions.
  • The tool enhances the scalability and efficiency of genome-wide RNA interaction studies.
  • RIsearch serves as a valuable pre-filter for miRNA target prediction and bacterial RNA-RNA interaction analysis.