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Published on: October 4, 2018
The topological relationship between the large-scale attributes and local interaction patterns of complex networks
1Department of Physics and Center for Complex Network Research, University of Notre Dame, Notre Dame, IN 46556, USA.
Summary
Complex networks contain recurring interaction patterns called subgraphs. This study reveals how subgraph abundance and clustering are linked to network organization, impacting function and structure.
Area of Science:
- Network science
- Systems biology
- Graph theory
Background:
- Recurring subgraph patterns in complex networks hold functional and organizational information.
- The reasons for varying subgraph quantities, clustering, and their relation to global network organization are not well understood.
Purpose of the Study:
- To investigate the mutual relationship between large-scale network topology and local subgraph structure.
- To identify distinct classes of subgraphs and their aggregation behaviors.
Main Methods:
- Analysis of subgraph abundance and clustering in five well-studied cellular networks.
- Direct measurements to confirm the interplay between topological organization and subgraph structure.
Main Results:
- Network topology and local subgraph structure mutually define and predict each other.
- Two distinct subgraph classes were identified: type I and type II.
- Type I subgraphs, unlike type II, inherently aggregate into clusters and cannot exist in isolation.
Conclusions:
- A topological framework explains subgraph abundance and clustering in complex networks.
- This framework offers insights into the origin and function of subgraphs across various network types.
- Understanding subgraph dynamics is crucial for comprehending complex system organization.
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