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

MicroRNAs01:22

MicroRNAs

3.2K
MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
3.2K
Ribosome Profiling02:24

Ribosome Profiling

3.7K
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...
3.7K
Experimental RNAi02:15

Experimental RNAi

6.4K
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...
6.4K
Riboswitches01:56

Riboswitches

8.8K
Riboswitches are non-coding mRNA domains that regulate the transcription and translation of downstream genes without the help of proteins. Riboswitches bind directly to a metabolite and can form unique stem-loop or hairpin structures in response to the amount of the metabolite present. They have two distinct regions – a metabolite-binding aptamer and an expression platform.
The aptamer has high specificity for a particular metabolite which allows riboswitches to specifically regulate...
8.8K
Alternative RNA Splicing02:18

Alternative RNA Splicing

21.9K
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...
21.9K
CRISPR and crRNAs02:53

CRISPR and crRNAs

17.8K
Bacteria and archaea are susceptible to viral infections just like eukaryotes; therefore, they have developed a unique adaptive immune system to protect themselves. Clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins (CRISPR-Cas) are present in more than 45% of known bacteria and 90% of known archaea.
The CRISPR-Cas system stores a copy of foreign DNA in the host genome and uses it to identify the foreign DNA upon reinfection. CRISPR-Cas has three different...
17.8K

You might also read

Related Articles

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

Sort by
Same author

Inferring statistical trends of the COVID19 pandemic from current data. Where probability meets fuzziness.

Information sciences·2021
Same author

Learning by Asymmetric Parallel Boltzmann Machines.

Neural computation·2019
Same author

Editorial--special issue on autonomous learning.

Neural networks : the official journal of the International Neural Network Society·2013
Same author

Mobility timing for agent communities, a cue for advanced connectionist systems.

IEEE transactions on neural networks·2011
Same author

A feed-forward neural logic based on synaptic and volume transmission.

Brain research reviews·2007
Same author

A general framework for learning rules from data.

IEEE transactions on neural networks·2004
Same journal

Identification of long non-coding RNAs involved in leukemogenesis and venetoclax response in acute myeloid leukemia through functional CRISPR-dCas9 interference screens.

Non-coding RNA research·2026
Same journal

LncRNA MIR22HG and miR-10a-5p: Pioneering serum biomarkers for pancreatic cancer diagnosis and progression assessment.

Non-coding RNA research·2026
Same journal

CRISPR decodes the RNA regulatory network in prostate cancer: A review from mechanisms to precision therapeutics.

Non-coding RNA research·2026
Same journal

tRNA-derived small RNAs in ocular neovascular diseases: A systematic review.

Non-coding RNA research·2026
Same journal

Discovery of a G-rich ultra stable human ncRNA G-quadruplex that binds ATP.

Non-coding RNA research·2026
Same journal

Functional role of long non-coding RNA MALAT1 and HOTAIR in lung cancer.

Non-coding RNA research·2026
See all related articles

Related Experiment Video

Updated: Oct 15, 2025

mirMachine: A One-Stop Shop for Plant miRNA Annotation
06:16

mirMachine: A One-Stop Shop for Plant miRNA Annotation

Published on: May 1, 2021

2.7K

A holistic miRNA-mRNA module discovery.

Ghada Shommo1, Bruno Apolloni2

  • 1Sudan University of Science and Technology, Department of Information Technology and Computer Science, Sudan.

Non-Coding RNA Research
|October 27, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new computational method to identify microRNA-messenger RNA modules involved in gene regulation. The approach aids in discovering novel regulatory interactions for various diseases.

Keywords:
Hausdorff linkageHolistic approachIndirect targetingNon-differentially-expressed genesNon-predicted targetsmiRNA-mRNA modules

More Related Videos

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
09:29

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools

Published on: August 21, 2019

7.6K
Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay
12:49

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Published on: May 25, 2015

10.2K

Related Experiment Videos

Last Updated: Oct 15, 2025

mirMachine: A One-Stop Shop for Plant miRNA Annotation
06:16

mirMachine: A One-Stop Shop for Plant miRNA Annotation

Published on: May 1, 2021

2.7K
A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
09:29

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools

Published on: August 21, 2019

7.6K
Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay
12:49

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Published on: May 25, 2015

10.2K

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Micro-RNAs (miRNAs) regulate messenger RNA (mRNA) gene expression.
  • Existing methods for identifying miRNA-mRNA regulatory modules have limitations.
  • Understanding these interactions is crucial for disease research.

Purpose of the Study:

  • To propose a holistic computational procedure for identifying miRNA-mRNA modules.
  • To address limitations in current methods for module discovery.
  • To enable the discovery of novel regulatory interactions.

Main Methods:

  • A novel strategy postpones decision-making on module components until biological exploitation.
  • Employs sequences of evolving metrics instead of statistical tests.
  • Requires high-performance computing (HPC) for computational intensity.

Main Results:

  • The procedure was successfully implemented on a Multiple Myeloma dataset.
  • Identified potential new miRNA-mRNA modules, including those with non-differentially expressed components.
  • Demonstrated the discovery of pairs with genes not previously considered targeted.

Conclusions:

  • The developed procedure effectively identifies miRNA-mRNA modules.
  • The method is computationally manageable and scalable.
  • Suggests broad applicability to diseases involving miRNA-mRNA interactions.