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

4.2K
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...
4.2K
MicroRNAs01:22

MicroRNAs

24.4K
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...
24.4K
Nucleic Acid Structure01:25

Nucleic Acid Structure

9.7K
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...
9.7K
RNA Interference01:23

RNA Interference

28.3K
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...
28.3K
Protein-protein Interfaces02:04

Protein-protein Interfaces

14.9K
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...
14.9K

You might also read

Related Articles

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

Sort by
Same author

Long intergenic non-protein coding RNA-467 targets microRNA-451a in human colorectal cancer.

Oncology letters·2020
Same author

Reduced skeletal muscle independently predicts 1-year aggravated joint destruction in patients with rheumatoid arthritis.

Therapeutic advances in musculoskeletal disease·2020
Same author

LncRNA <i>Malat1</i> inhibition of TDP43 cleavage suppresses IRF3-initiated antiviral innate immunity.

Proceedings of the National Academy of Sciences of the United States of America·2020
Same author

Correlation between serum bilirubin levels and the severity as well as the prognosis of idiopathic pulmonary fibrosis.

Chronic respiratory disease·2020
Same author

Higher Cortical Dysfunction Presenting as Visual Symptoms in Neurodegenerative Diseases.

Frontiers in neurology·2020
Same author

Effect of Renal Denervation on Cardiac Function and Inflammatory Factors in Heart Failure After Myocardial Infarction.

Journal of cardiovascular pharmacology·2020
Same journal

Isolation of Mesenchymal Stem Cell-Derived Extracellular Vesicles.

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

Modeling Melanoma Immune Surveillance by CAR-T Cells in Human Skin Organoids.

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

Stepwise Optimization of a Matrigel-Based In Vitro Angiogenesis Assay for Reproducible and Quantifiable 2D-Tube Formation Using HUVECs.

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

Quantifying Mechanical Properties of Fresh Ovarian Tissue with Optical Brillouin Microscopy.

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

3D Chromatin Architecture During Early Development: New Methods and New Findings.

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

Metabolic Plasticity in Embryogenesis Throughout the Lens of NAD<sup></sup>.

Methods in molecular biology (Clifton, N.J.)·2026
See all related articles

Related Experiment Video

Updated: Mar 3, 2026

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs
11:00

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Published on: June 12, 2018

14.6K

Predicting Functional MicroRNA-mRNA Interactions.

Zixing Wang1, Yin Liu2,3

  • 1University of Texas M.D. Anderson Cancer Center, 77455 Fannin Street, Houston, TX, USA.

Methods in Molecular Biology (Clifton, N.J.)
|April 26, 2017
PubMed
Summary
This summary is machine-generated.

Identifying microRNA (miRNA) targets is crucial for understanding gene regulation. A new regularized regression model integrates sequence and expression data to accurately detect miRNA targets and their regulatory effects.

Keywords:
Context scoreMiRNA target identificationRegularized regressionSequence featuresThermodynamic stabilitymiRNA and mRNA expression profiles

More Related Videos

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library
08:40

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

Published on: April 6, 2012

18.1K
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

10.5K

Related Experiment Videos

Last Updated: Mar 3, 2026

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs
11:00

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Published on: June 12, 2018

14.6K
Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library
08:40

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

Published on: April 6, 2012

18.1K
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

10.5K

Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • MicroRNAs (miRNAs) are small RNA molecules regulating gene expression.
  • miRNAs target messenger RNAs (mRNAs) for degradation or translation inhibition.
  • Identifying miRNA targets is essential for understanding biological processes and diseases.

Purpose of the Study:

  • To develop a novel computational approach for identifying miRNA targets.
  • To integrate sequence information with expression profiles for accurate target detection.
  • To quantify miRNA-mediated gene down-regulation and identify key sequence features.

Main Methods:

  • A regularized regression approach was employed.
  • Integration of miRNA and mRNA expression profiles with miRNA target site sequence features.
  • Consideration of thermodynamic stability, accessibility energy, and context features of target sites.

Main Results:

  • The model quantifies the down-regulation effect of miRNAs on their targets.
  • It estimates the contribution of sequence features in predicting functional miRNA-mRNA interactions.
  • Accurate detection of miRNA targets was achieved by integrating diverse data types.

Conclusions:

  • The developed method provides a robust approach for miRNA target identification.
  • This method enhances the understanding of miRNA regulatory mechanisms.
  • It facilitates the study of miRNA roles in health and disease pathogenesis.