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

Protein Networks02:26

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 Analysis01:10

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...
Node Analysis for AC Circuits01:14

Node Analysis for AC Circuits

Consider an angioplasty system featuring a catheter equipped with a turbine, a critical tool for removing plaque deposits from coronary arteries. This intricate medical device operates using a circuit model reminiscent of a dual-node RLC circuit powered by a current-controlled voltage source.
To unravel the complexities of this system, nodal analysis is employed, a powerful technique founded on Kirchhoff's current law (KCL), which remains valid for phasors. AC circuits can effectively be...
Nodal Analysis with Voltage Sources01:11

Nodal Analysis with Voltage Sources

Nodal analysis is a remarkably effective method used in electrical engineering to simplify the analysis of complex circuits, including those with dependent or independent voltage sources. Its strength lies in its systematic approach to breaking down circuits into manageable components, making it easier for engineers to understand and solve.
Consider a circuit that contains four resistors and two voltage sources, as shown in Figure 1. One of these voltage sources is connected between a...
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a survival tree begins...
Circuit Terminology01:14

Circuit Terminology

An electrical network is a system composed of interconnected elements, such as resistors, capacitors, inductors, and voltage or current sources. Unlike a circuit, an electrical network does not necessarily form a closed path. In other words, while all circuits can be considered networks due to their interconnected nature, not every network qualifies as a circuit.
A circuit, on the other hand, is also an interconnected system of electrical elements but must contain one or more closed paths.

You might also read

Related Articles

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

Sort by
Same author

Lost in Retraining: Closed-Loop Learning and Model Collapse in Exponential Families.

Physical review letters·2026
Same author

What leads to vaccine compliance? Evidence from healthcare workers.

Journal of public health research·2026
Same author

Designing topological cluster synchronization patterns with the Dirac operator.

Physical review. E·2026
Same author

Triadic percolation on multilayer networks.

Physical review. E·2026
Same author

Beyond binary: a machine-learning classification of childhood COVID-19 vaccination intentions using behavioural data.

Population health metrics·2025
Same author

Neighbourhood topology unveils pathological hubs in the brain networks of epilepsy-surgery patients.

Brain communications·2025
Same journal

Tau protein as a regulator of mitochondrial function and dynamics.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

A scalable, dividing cell model for the robust propagation and quantification of human sporadic Creutzfeldt-Jakob disease prions.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Epigenetic regulation of mesenchymal BMP signaling directs postnatal organ innervation.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Single-shot wide-field biochemical imaging at 1 kHz frame rate.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Morphogenesis and topological evolution of a frustrated nematic liquid crystal under confinement.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

B cell-intrinsic CXCR3 drives efficient generation of ectopic pulmonary germinal center responses to influenza A virus infection.

Proceedings of the National Academy of Sciences of the United States of America·2026
See all related articles

Related Experiment Video

Updated: Jun 22, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Assessing the relevance of node features for network structure.

Ginestra Bianconi1, Paolo Pin, Matteo Marsili

  • 1Abdus Salam International Center for Theoretical Physics, Strada Costiera 11, 34014 Trieste, Italy.

Proceedings of the National Academy of Sciences of the United States of America
|July 3, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces Theta, a new entropy-based measure to analyze how node characteristics influence network structure. It helps identify essential features in complex systems like social networks and biological interactions.

More Related Videos

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

Related Experiment Videos

Last Updated: Jun 22, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

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

Area of Science:

  • Complex systems analysis
  • Network science
  • Information theory

Background:

  • Real-world networks possess nodes with both connections and attributes (e.g., age, protein abundance, location).
  • Understanding how node characteristics shape network structure is vital for distinguishing important features from irrelevant ones.

Purpose of the Study:

  • To propose a general indicator, Theta, for quantifying the dependence of network structure on node features.
  • To provide a method for integrating connection information with node characteristics.

Main Methods:

  • Development of a general indicator, Theta, based on entropy measures.
  • Application of Theta to diverse real-world networks: U.S. school friendships, Saccharomyces cerevisiae protein interactions, and U.S. airport network.

Main Results:

  • The proposed Theta measure quantifies the influence of node characteristics on network structure.
  • Demonstrated Theta's utility across social, biological, and technological networks.
  • Showcased that Theta provides complementary insights compared to existing network measures.

Conclusions:

  • Theta offers a novel approach to understanding feature-dependent network structures.
  • The measure is broadly applicable to various complex systems.
  • This entropy-based method enhances the analysis of network properties and node importance.