Related Experiment Video
Updated: Jun 28, 2026
05:30
Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke
Published on: October 10, 2025
Comment on "properties of highly clustered networks"
Istvan Z Kiss1, Darren M Green
1Department of Mathematics, University of Sussex, Falmer, Brighton BN1 9RF, United Kingdom. i.z.kiss@sussex.ac.uk
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|November 13, 2008
Summary
Clustered networks show a lower epidemic threshold due to degree distribution, not clustering alone. Rewiring conserves degree distribution, closely reproducing the low threshold in networks with minimal clustering.
Area of Science:
- Network science
- Epidemiology
- Complex systems
Background:
- The study examines Newman's clustered network generation procedure.
- Previous work linked clustered networks to lower epidemic thresholds in susceptible-infective-recovered (SIR) dynamics.
- This research investigates the underlying mechanisms of this phenomenon.
Discussion:
- Rewiring clustered networks while conserving degree distribution reproduced the low epidemic threshold.
- This suggests that degree distribution, rather than clustering itself, is the primary driver of the lowered threshold.
- The analysis highlights how clustering influences degree heterogeneity and network structure.
Key Insights:
- The lower epidemic threshold observed in clustered networks is primarily attributable to their heterogeneous degree distributions.
- Networks with high clustering exhibit increased node degree variability and a higher prevalence of isolated nodes.
- Rewiring preserves the degree distribution, demonstrating that the observed epidemic threshold is linked to this distribution, not clustering per se.
Outlook:
- Further research can explore the interplay between network topology and epidemic spread in various network models.
- Investigating how different rewiring strategies impact epidemic thresholds could yield new insights.
- Understanding these relationships is crucial for designing effective public health interventions in complex networks.
Related Concept Videos
02:26Protein 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,...
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,...
02:26Protein 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,...
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,...
02:18Network Covalent Solids
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
01:20Cluster Sampling Method
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
01:25Network Function of a Circuit
Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
01:45Vesicular Tubular Clusters
After budding out from the ER membrane, some COPII vesicles lose their coat and fuse with one another to form larger vesicles and interconnected tubules called vesicular tubular clusters or VTCs. These clusters constitute a compartment at the ER-Golgi interface known as ERGIC (Endoplasmic Reticulum Golgi Intermediate Compartment). The ERGIC is a mobile membrane-bound cargo transport system that sorts proteins secreted from ER and delivers them to the Golgi.
With the help of motor proteins such...
With the help of motor proteins such...