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

3.0K
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...
3.0K
Protein Networks02:26

Protein Networks

3.9K
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,...
3.9K
RNA Interference01:23

RNA Interference

26.0K
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...
26.0K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.5K
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...
12.5K

You might also read

Related Articles

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

Sort by
Same authorSame journal

Functionally Guided Graph Learning for Robust Cross-Patient Cell-Type Annotation in Single-Cell RNA Sequencing.

Journal of chemical information and modeling·2026
Same author

Evaluation of the therapeutic effect of new hypoglycemic drugs on patients with heart failure with reduced ejection fraction and type 2 diabetes: a systematic review and network meta-analysis.

Frontiers in cardiovascular medicine·2026
Same author

ASTWAS: modeling alternative polyadenylation and SNP effects in kernel-driven TWAS reveal novel genetic associations for complex traits.

Briefings in bioinformatics·2026
Same author

TAPB: an interventional debiasing framework for alleviating target prior bias in drug-target interaction prediction.

Nature communications·2025
Same author

A Multisource Transformer-Guided Graph Representation Learning Framework for circRNA-Disease Association Prediction.

ACS omega·2025
Same author

Survey and analysis of the prevalence of tobacco use among patients with severe mental illness at a tertiary specialized psychiatric medical center in China.

Frontiers in psychiatry·2025

Related Experiment Video

Updated: Jun 14, 2025

In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions
10:27

In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions

Published on: October 21, 2022

1.5K

RBNE-CMI: An Efficient Method for Predicting circRNA-miRNA Interactions via Multiattribute Incomplete Heterogeneous

Chang-Qing Yu1, Xin-Fei Wang2, Li-Ping Li3

  • 1School of Information Engineering, Xijing University, Xi'an 710123 China.

Journal of Chemical Information and Modeling
|September 4, 2024
PubMed
Summary

This study introduces RBNE-CMI, a novel computational method for predicting circular RNA-microRNA interactions. It effectively models incomplete biological networks, improving prediction accuracy for disease biomarkers.

More Related Videos

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

2.3K
Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
07:35

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Published on: December 1, 2023

611

Related Experiment Videos

Last Updated: Jun 14, 2025

In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions
10:27

In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions

Published on: October 21, 2022

1.5K
CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

2.3K
Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
07:35

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Published on: December 1, 2023

611

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Circular RNA (circRNA)-microRNA (miRNA) interactions (CMI) are vital in cellular regulation and disease.
  • Accurate CMI prediction is crucial for developing new diagnostic and therapeutic strategies.
  • Existing computational methods struggle with incomplete data and large-scale modeling of molecules with diverse attributes.

Purpose of the Study:

  • To develop an effective computational method for predicting circRNA-miRNA interactions.
  • To introduce a framework for embedding incomplete multiattribute CMI heterogeneous networks.
  • To improve the efficiency and performance of CMI prediction.

Main Methods:

  • Proposed a novel method named RBNE-CMI.
  • Developed a framework to embed incomplete multiattribute CMI heterogeneous networks.
  • Integrated diverse CMI datasets into a unified incomplete network for modeling.

Main Results:

  • RBNE-CMI achieved superior performance in 5-fold cross-validation compared to existing models.
  • The method demonstrated better performance even on complete datasets.
  • Successfully predicted 18 out of 20 potential cancer biomarkers in a case study.

Conclusions:

  • RBNE-CMI offers an effective solution for predicting circRNA-miRNA interactions using incomplete network data.
  • The proposed framework enhances the modeling of complex molecular interactions.
  • This approach holds significant potential for advancing disease diagnosis and therapy through accurate CMI prediction.