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

Stability of structures01:14

Stability of structures

623
In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
623
Protein Networks02:26

Protein Networks

4.7K
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,...
4.7K
Protein Networks02:26

Protein Networks

2.9K
2.9K
Circuit Terminology01:14

Circuit Terminology

3.3K
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.
3.3K
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

644
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
644
Reliability and Validity01:29

Reliability and Validity

14.4K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
14.4K

You might also read

Related Articles

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

Sort by
Same author

Beta-blocker Therapy after Myocardial Infarction without Reduced Ejection Fraction: An EF-stratified Reappraisal in the Contemporary Era.

Current cardiology reports·2026
Same author

Knowledge and use of digital technologies in periodontal practices in the United States: A survey study.

Journal of periodontology·2025
Same author

Trial of an Inexpensive Training Simulation Model for Laparoscopic Appendicectomy.

Cureus·2024
Same author

Results of shared learning of a new radiofrequency identification localization device-a UK iBRA-NET breast cancer localisation study.

Clinical radiology·2024
Same author

Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support.

The international journal of high performance computing applications·2024
Same author

Toward mechanistic medical digital twins: some use cases in immunology.

Frontiers in digital health·2024
Same journal

Tension on dsDNA bound to ssDNA-RecA filaments may play an important role in driving efficient and accurate homology recognition and strand exchange.

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Amplitude-phase coupling drives chimera states in globally coupled laser networks [Phys. Rev. E 91, 040901(R) (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Shapes of sedimenting soft elastic capsules in a viscous fluid [Phys. Rev. E 92, 033003 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Attenuation of excitation decay rate due to collective effect [Phys. Rev. E 90, 022142 (2014)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Role of connectivity and fluctuations in the nucleation of calcium waves in cardiac cells [Phys. Rev. E 92, 052715 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Lattice Boltzmann approach for complex nonequilibrium flows [Phys. Rev. E 92, 043308 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
See all related articles

Related Experiment Video

Updated: Apr 12, 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

1.7K

Analyzing network reliability using structural motifs.

Yasamin Khorramzadeh1, Mina Youssef2, Stephen Eubank3

  • 1Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia 24061, USA and Department of Physics, Virginia Tech, Blacksburg, Virginia 24061, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|May 15, 2015
PubMed
Summary
This summary is machine-generated.

This study analyzes how network structure impacts disease spread using the reliability polynomial. It introduces structural motifs to better understand how network properties influence diffusion dynamics.

More Related Videos

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
07:55

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

10.8K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.8K

Related Experiment Videos

Last Updated: Apr 12, 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

1.7K
Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
07:55

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

10.8K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.8K

Area of Science:

  • Network science
  • Mathematical modeling
  • Epidemiology

Background:

  • The spread of infectious diseases and other diffusive phenomena is heavily influenced by the underlying network structure.
  • Understanding these network effects is crucial for predicting and controlling diffusion processes.

Purpose of the Study:

  • To analyze the effect of network structure on diffusive dynamics using the reliability polynomial.
  • To introduce a novel representation of the reliability polynomial based on structural motifs.

Main Methods:

  • Utilizing the reliability polynomial, originally developed by Moore and Shannon in 1956.
  • Representing the reliability polynomial in terms of "structural motifs" derived from network topology.

Main Results:

  • Demonstrated a method to represent the reliability polynomial using structural motifs.
  • Established a framework for reasoning about how network structure influences diffusion.

Conclusions:

  • Network structure significantly impacts diffusive dynamics, such as disease spread.
  • The proposed structural motif representation facilitates analysis of network effects on diffusion.