Jove
Visualize
Contact Us
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 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...
Experimental RNAi02:15

Experimental RNAi

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...
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...
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...
Alternative RNA Splicing02:18

Alternative RNA Splicing

Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...
Alternative RNA Splicing02:18

Alternative RNA Splicing

Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...

You might also read

Related Articles

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

Sort by
Same author

Controllable protein design via autoregressive direct coupling analysis conditioned on principal components.

PLoS computational biology·2026
Same author

Sampling the space of solutions of an artificial neural network.

Physical review. E·2025
Same author

The advantage of periodic over constant signalling in microRNA-mediated regulation.

Nucleic acids research·2025
Same author

A competition network connects Rab5 and Rab11 GTPases at the surface of endocytic structures.

iScience·2025
Same author

Reconstruction of Ancestral Protein Sequences Using Autoregressive Generative Models.

Molecular biology and evolution·2025
Same author

Direct coupling analysis and the attention mechanism.

BMC bioinformatics·2025
Same journal

Invaders taking over-Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot.

PloS one·2026
Same journal

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways.

PloS one·2026
Same journal

Performance patterns and records in the world aquatics masters championships: Where do the most frequently represented nations among the top-ten masters swimmers come from?

PloS one·2026
Same journal

Modeling diurnal Temperature-Rainfall relationships under multicollinearity using PLS-SEM: A case study of Ghana.

PloS one·2026
Same journal

Organizational culture, social capital, and emergency capacity in primary healthcare institutions: A cross-sectional structural equation modeling study comparing ordinary and older communities.

PloS one·2026
Same journal

Impact of kidney function on the metabolome in the general population.

PloS one·2026
See all related articles

Related Experiment Video

Updated: May 9, 2026

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
12:54

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

Modelling Competing Endogenous RNA Networks.

Carla Bosia1, Andrea Pagnani, Riccardo Zecchina

  • 1Human Genetics Foundation (HuGeF), Torino, Italy.

Plos One
|July 11, 2013
PubMed
Summary
This summary is machine-generated.

MicroRNAs (miRNAs) regulate gene networks and are implicated in disease. This study models miRNA-mRNA interactions, revealing a robust competing RNA (ceRNA) mechanism with unique threshold dynamics and cross-talk effects.

Related Experiment Videos

Last Updated: May 9, 2026

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
12:54

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

Area of Science:

  • Molecular Biology
  • Systems Biology
  • Biophysics

Background:

  • MicroRNAs (miRNAs) are key post-transcriptional regulators involved in gene networks.
  • Aberrant miRNA activity is linked to various diseases.
  • miRNA-target interactions can be described by titration mechanisms, leading to competing endogenous RNA (ceRNA) effects.

Purpose of the Study:

  • To develop a stochastic model for analyzing miRNA-mRNA interaction networks.
  • To investigate the equilibrium and non-equilibrium properties of these networks, particularly near titration thresholds.
  • To characterize phenomena such as cross-talk, robustness, and response times.

Main Methods:

  • Stochastic modeling of miRNA-mRNA interactions.
  • Analysis of equilibrium and out-of-equilibrium system properties.
  • Investigation of network dynamics near equimolarity thresholds.

Main Results:

  • Detailed description of phenomena near the titration threshold.
  • Identification of maximal cross-talk and correlation between mRNA targets.
  • Demonstration of the robustness of the ceRNA effect against parameter variations, including interaction catalysis.
  • Observation of anomalous response-time dynamics to external perturbations.

Conclusions:

  • The proposed stochastic model accurately describes complex miRNA-mRNA regulatory networks.
  • The ceRNA mechanism exhibits robust characteristics and unique dynamic behaviors near critical thresholds.
  • Understanding these dynamics is crucial for comprehending gene regulation and disease development.