Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Protein Networks

Protein Networks

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,...

Nodal Analysis

Nodal Analysis

Nodal analysis is a fundamental method in electrical engineering used to simplify the process of circuit analysis. This method revolves around the concept of using node voltages as the primary variables for circuit analysis. The objective is to determine the voltage at each node in a circuit, which can then be used to find other quantities of interest, such as currents through specific components.
Consider, for instance, a simple circuit composed of three nodes and three resistors, as shown in...

You might also read

Related Articles

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

Sort by

Same author

Manipulating the Photoluminescence Pathway in Metal Nanoclusters by Atomic Structural Editing.

Small (Weinheim an der Bergstrasse, Germany)·2026

Same author

Perianal lidocaine application during unsedated colonoscopy: A double-blind randomized controlled trial.

PloS one·2026

Same author

A single-cell multi-omics atlas defines the cellular and molecular landscape of gastric intestinal metaplasia.

Journal of translational medicine·2026

Same author

Dual generative adversarial graph networks: Unsupervised and semi-supervised learning with spherical graph embeddings.

Neural networks : the official journal of the International Neural Network Society·2026

Same author

Neural topic modeling on hyperspheres: Spherical representation learning with von Mises-Fisher mixtures.

Neural networks : the official journal of the International Neural Network Society·2026

Same author

The impact of cumulative low-density lipoprotein cholesterol on prognosis in coronary heart disease patients: A retrospective study based on time-weighted cumulative exposure.

Journal of clinical lipidology·2026

Same journal

A tri-axis optomechanical accelerometer with plasmonic MIM waveguide and structural direction-dependent optical signatures.

Scientific reports·2026

Same journal

Holographic leaky-wave antennas with independently controlled multiple counter-rotating vortex beams.

Scientific reports·2026

Same journal

Differential associations of longitudinal hearing and vision trajectories with dementia and mild cognitive impairment in older adults.

Scientific reports·2026

Same journal

Abdominal obesity and leisure-time sedentary behavior in relation to gastroesophageal reflux disease risk: a prospective cohort study from the UK Biobank.

Scientific reports·2026

Same journal

Effect of nitrogen-rich COF incorporation on the structure and separation performance of polyamide nanofiltration membranes.

Scientific reports·2026

Same journal

Withanolide A inhibits hIAPP aggregation: An In silico, biophysical, and drosophila-based In vivo validation.

Scientific reports·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Oct 12, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

A new model to identify node importance in complex networks based on DEMATEL method.

Wentao Fan¹, Yuhuan He², Xiao Han³

¹Department of Control and Systems Engineering, Nanjing University, Nanjing, 210093, China. fanwentaoswu@163.com.

Scientific Reports

|November 25, 2021

Summary

This summary is machine-generated.

Identifying node importance in complex networks is crucial. This study introduces a new model using Decision-making Trial and Evaluation Laboratory (DEMATEL) to effectively combine local and global network information for accurate node assessment.

More Related Videos

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Related Experiment Videos

Last Updated: Oct 12, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Area of Science:

Network Science
Complex Systems Analysis
Graph Theory Applications

Background:

Identifying node importance is a key challenge in complex networks.
Existing methods often neglect the integration of local and global network information.
A comprehensive approach is needed to accurately assess node significance within a system.

Purpose of the Study:

To propose a novel model for identifying node importance in complex networks.
To leverage the Decision-making Trial and Evaluation Laboratory (DEMATEL) method for a holistic analysis.
To improve upon existing methods by effectively combining local and global network characteristics.

Main Methods:

Development of a new node importance identification model.
Application of the Decision-making Trial and Evaluation Laboratory (DEMATEL) method, which utilizes graph theory.
Experimental validation using the susceptible-infected (SI) model for comparative analysis.

Main Results:

The proposed DEMATEL-based model effectively considers global network information.
Experimental results demonstrate the superiority of the new model compared to existing methods.
The model's effectiveness is validated across three diverse network applications.

Conclusions:

The DEMATEL-based model offers a robust approach to identifying node importance.
Integrating global information significantly enhances the accuracy of node significance assessment.
This method provides a valuable tool for analyzing complex systems.