Jove
Visualize
Contact Us

Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

15.1K
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...
15.1K
RNA Interference01:23

RNA Interference

29.0K
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...
29.0K
Protein Networks02:26

Protein Networks

4.7K
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,...
4.7K
Experimental RNAi02:15

Experimental RNAi

8.4K
RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
8.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

ShaKer: RNA SHAPE prediction using graph kernel.

Bioinformatics (Oxford, England)·2019
Same author

Integration of accessibility data from structure probing into RNA-RNA interaction prediction.

Bioinformatics (Oxford, England)·2018
Same author

Evaluating the quality of SHAPE data simulated by k-mers for RNA structure prediction.

Journal of bioinformatics and computational biology·2017
Same author

RNA design using simulated SHAPE data.

Genes & genetic systems·2017
Same author

Evolutionary Algorithm for RNA Secondary Structure Prediction Based on Simulated SHAPE Data.

PloS one·2016
Same author

RNA secondary structure prediction based on SHAPE data in helix regions.

Journal of theoretical biology·2015
Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Characterization of Bioactive Saponins from Sea Cucumbers.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

Methods in molecular biology (Clifton, N.J.)·2026
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Apr 18, 2026

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA
07:24

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Published on: July 9, 2021

2.7K

Fast prediction of RNA-RNA interaction using heuristic algorithm.

Soheila Montaseri1

  • 1Department of mathematics, Statistics and Computer Sciences, University of Tehran, Tehran, Iran, soheila.montaseri@gmail.com.

Methods in Molecular Biology (Clifton, N.J.)
|January 12, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a fast heuristic algorithm to predict RNA-RNA interactions, crucial for gene regulation. The parallelized method accurately identifies binding sites with low computational time.

More Related Videos

A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA
13:00

A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA

Published on: December 2, 2009

12.3K
RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

32.5K

Related Experiment Videos

Last Updated: Apr 18, 2026

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA
07:24

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Published on: July 9, 2021

2.7K
A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA
13:00

A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA

Published on: December 2, 2009

12.3K
RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

32.5K

Area of Science:

  • Computational Biology
  • Molecular Biology
  • Bioinformatics

Background:

  • RNA-RNA interactions are vital for biological processes, including gene expression regulation.
  • Predicting these interactions is essential, but existing algorithms often suffer from high computational costs.
  • RNA molecules can inhibit translation by forming stable interactions with other RNAs.

Purpose of the Study:

  • To develop an accurate and efficient heuristic algorithm for predicting RNA-RNA interaction structures.
  • To address the computational time challenge associated with RNA-RNA interaction prediction.
  • To present a parallelized version of the heuristic method for multicore architectures.

Main Methods:

  • A heuristic approach utilizing minimum free energy (MFE) for RNA-RNA interaction prediction.
  • Employing dot matrices to determine RNA secondary structures and identify binding sites.
  • Implementing a parallelized version of the algorithm to leverage multicore processing capabilities.

Main Results:

  • The proposed algorithm accurately predicts RNA-RNA interaction structures.
  • The parallelized method demonstrates high efficiency and validity on tested datasets.
  • The approach significantly reduces computational time compared to existing methods.

Conclusions:

  • The developed heuristic algorithm offers a valid and efficient solution for RNA-RNA interaction prediction.
  • Parallelization enhances the algorithm's performance, making it suitable for complex biological analyses.
  • This method provides a low-computational-time alternative for studying RNA-RNA interactions in organisms like Escherichia coli.