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

Contact-dependent Signaling

Contact-dependent Signaling

Contact-dependent signaling, as the name suggests, requires that communicating cells be in direct contact with each other. This is achieved either through receptor-ligand interactions or by specialized cytoplasmic channels that allow the flow of small molecules between cells. In animal cells, channels called gap junctions facilitate contact-dependent signaling in certain tissues, whereas, plasmodesmata perform a similar function in plants.
Gap Junctions
In animal cells, gap junctions are formed...

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,...

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,...

Distributed Loads: Problem Solving

Distributed Loads: Problem Solving

Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...

Protein-protein Interfaces

Protein-protein Interfaces

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 polypeptide...

Protein-Protein Interfaces

Protein-Protein Interfaces

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 polypeptide...

You might also read

Related Articles

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

Sort by

Same author

Idiopathic hypereosinophilic syndrome with hepatic sinusoidal obstruction syndrome: A case report and literature review.

World journal of gastrointestinal surgery·2023

Same author

Corneal endothelial regeneration in human eyes using endothelium-free grafts.

BMC ophthalmology·2022

Same author

Susceptible-infected-susceptible model on networks with eigenvector localization.

Physical review. E·2020

Same author

Epidemic spreading on hierarchical geographical networks with mobile agents.

Communications in nonlinear science & numerical simulation·2020

Same author

Sampling-based box-covering algorithm for renormalization of networks.

Chaos (Woodbury, N.Y.)·2019

Same author

Synaptic modifications driven by spike-timing-dependent plasticity in weakly coupled bursting neurons.

Physical review. E·2019

Search research articles

Related Experiment Videos

Optimal contact process on complex networks.

Rui Yang¹, Tao Zhou, Yan-Bo Xie

¹Department of Electrical Engineering, Arizona State University, Tempe, Arizona 85287, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|March 5, 2009

Summary

This summary is machine-generated.

To maximize spreading on complex networks, contact probability should be inversely proportional to node degree. This strategy highlights the crucial role of low-degree nodes, challenging the common belief in the importance of hubs for network dynamics.

Related Experiment Videos

Area of Science:

Statistical Physics
Network Science
Complex Systems

Background:

Contact processes on complex networks are vital in nonequilibrium statistical physics.
These processes have significant applications in epidemiology and computer/communication networks.
Optimizing spreading dynamics on these networks is a fundamental challenge.

Purpose of the Study:

To identify a universal strategy for maximizing spreading efficiency in contact processes on complex networks.
To investigate the relationship between node degree and contact probability for optimal spread.

Main Methods:

Theoretical analysis of contact process dynamics.
Mathematical modeling of contact probability as a function of node degree (W(k)).
Computational verification using both model and real-world network datasets.

Main Results:

A universal spreading maximization strategy is identified: contact probability inversely proportional to node degree (W(k) ~ k{-1}).
This strategy optimizes spreading by leveraging the connectivity patterns of nodes.
Small-degree nodes play a critical role in enhancing overall network spreading.

Conclusions:

The optimal strategy for spreading on complex networks involves prioritizing interactions with lower-degree nodes.
This finding contrasts with the conventional understanding that high-degree nodes (hubs) are solely responsible for efficient spreading.
The study underscores the importance of network topology, specifically node degree distribution, in controlling epidemic or information spread.