A Publish-Subscribe Model of Genetic Networks
2008

A Publish-Subscribe Model of Genetic Networks

publication Evidence: moderate

Author Information

Author(s): Calcott Brett, Balcan Duygu, Hohenlohe Paul A.

Primary Institution: Australian National University

Hypothesis

How do regulatory connections among genes mediated by signaling molecules affect the properties and evolution of genetic networks?

Conclusion

The publish-subscribe model allows for significant evolvability in genetic networks, enabling them to adapt to different environments without changing their degree distribution.

Supporting Evidence

  • The model produces multimodal in-degree distributions that differ from simpler Boolean models.
  • Simulated evolution showed that single mutations can lead to multiple changes in regulatory connections.
  • The evolved networks maintained similar degree distributions to randomly generated networks despite changes in attractor properties.

Takeaway

This study shows that genes can communicate through a system where they publish signals and subscribe to others, which helps them evolve and adapt better to their surroundings.

Methodology

The study used simulations to explore the dynamics of genetic regulatory networks based on a publish-subscribe model, analyzing properties like degree distributions and attractor dynamics.

Limitations

The model assumes a fixed number of signaling molecules and does not account for the effects of stochasticity in gene product binding.

Digital Object Identifier (DOI)

10.1371/journal.pone.0003245

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