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

Relationship Formation02:12

Relationship Formation

40.1K
What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
40.1K
Protein Networks02:26

Protein Networks

4.0K
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,...
4.0K
Outliers and Influential Points01:08

Outliers and Influential Points

4.1K
An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
4.1K
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

123
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
123
Complexation Equilibria: Factors Influencing Stability of Complexes01:09

Complexation Equilibria: Factors Influencing Stability of Complexes

399
In complexation reactions, metal cations are the electron pair acceptors, and the ligands are the electron pair donors. The stability of the metal complexes depends primarily on the complexing ability of the central metal ion and the nature of the ligands. Generally, the complexing ability of the metal ion depends on the size and charge of the ion. As the metal ion size increases, the stability of the metal complexes decreases, provided that the valency of the metal ion and the ligands remain...
399
Conformity01:20

Conformity

45.2K
Conformity is the change in a person’s behavior to go along with the group, even if that person does not agree with the group.
45.2K

You might also read

Related Articles

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

Sort by
Same author

Can Pareto Optimality Be Evidence of Life?

Astrobiology·2026
Same author

<i>Prototaxites</i> fossils are structurally and chemically distinct from extinct and extant Fungi.

Science advances·2026
Same author

Linear simple cycle reservoirs at the edge of stability perform Fourier decomposition of the input driving signals.

Chaos (Woodbury, N.Y.)·2025
Same author

Strong connectivity in real directed networks.

Proceedings of the National Academy of Sciences of the United States of America·2023
Same author

Identification of Clinically Relevant HIV Vif Protein Motif Mutations through Machine Learning and Undersampling.

Cells·2023
Same author

Assessing risk in the retail environment during the COVID-19 pandemic.

Royal Society open science·2021
Same journal

Desert lizards modulate nutritional responses to match seasonal biological needs.

Royal Society open science·2026
Same journal

Multi-generational fidelity, ecological and social determinants of roosting in a cooperatively breeding bird (<i>Argya squamiceps</i>).

Royal Society open science·2025
Same journal

Multifaceted polarization and information reliability in climate change discussions on social media platforms.

Royal Society open science·2025
Same journal

Comparing the kinematics related to inflicted head injury between violent shaking of a 6-week-old and a 1-year-old infant surrogate.

Royal Society open science·2025
Same journal

Partner choice increases observed reciprocity-based cooperation but decreases unobserved stake-based cooperation.

Royal Society open science·2025
Same journal

Importation models for travel-related SARS-CoV-2 cases reported in Newfoundland and Labrador during the COVID-19 pandemic.

Royal Society open science·2025
See all related articles

Related Experiment Video

Updated: Jul 17, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

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

Published on: December 7, 2021

2.2K

Influence and influenceability: global directionality in directed complex networks.

Niall Rodgers1,2, Peter Tiňo3, Samuel Johnson1,4

  • 1School of Mathematics, University of Birmingham, Birmingham, UK.

Royal Society Open Science
|August 31, 2023
PubMed
Summary
This summary is machine-generated.

Understanding network influence requires analyzing hierarchical structure and global directionality. Trophic analysis reveals how these factors determine a network's influence and influenceability, applicable across diverse directed networks.

Keywords:
directed networksnetwork dynamicstrophic analysis

More Related Videos

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
08:43

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment

Published on: August 7, 2017

7.9K
Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes
10:10

Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes

Published on: October 4, 2018

8.9K

Related Experiment Videos

Last Updated: Jul 17, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

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

Published on: December 7, 2021

2.2K
Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
08:43

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment

Published on: August 7, 2017

7.9K
Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes
10:10

Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes

Published on: October 4, 2018

8.9K

Area of Science:

  • Network Science
  • Complex Systems Analysis
  • Graph Theory

Background:

  • Traditional network analysis often overlooks global architecture when assessing node importance.
  • Understanding influence and influenceability in directed networks is crucial for predicting system behavior.

Purpose of the Study:

  • To investigate the role of hierarchical structure and global directionality in directed networks.
  • To demonstrate how trophic analysis can explain network influence and influenceability.

Main Methods:

  • Application of trophic analysis to directed networks.
  • Measurement of hierarchical structure using trophic levels.
  • Quantification of global directionality via trophic coherence.

Main Results:

  • Influence and influenceability are determined by trophic hierarchy and global directionality.
  • Trophic hierarchy explains node reach, eigenvector centrality localization, and dynamics in opinion and game models.
  • Global directionality mediates these influence phenomena.

Conclusions:

  • Node hierarchy is essential for understanding network influence.
  • Global directionality is a key mediator of influence in directed networks.
  • Trophic analysis provides a framework applicable to diverse real-world directed networks.