Deterministic and stochastic population-level simulations of an artificial lac operon genetic network
2011

Simulating Cell Population Dynamics in an Artificial Lac Operon Network

publication Evidence: moderate

Author Information

Author(s): Stamatakis Michail, Zygourakis Kyriacos

Primary Institution: Rice University

Hypothesis

How do deterministic and stochastic dynamics affect the behavior of cell populations in an artificial lac operon genetic network?

Conclusion

Stochasticity can enhance phenotypic heterogeneity and influence population behavior in an artificial lac operon system.

Supporting Evidence

  • Stochasticity can create or destroy bimodality in cell populations.
  • The study provides insights for constructing simpler models of cell dynamics.
  • Deterministic models can yield different predictions compared to stochastic models.

Takeaway

This study shows that tiny changes in how cells behave can make a big difference in how a whole group of cells acts, especially in a lab-made system.

Methodology

The study used two Monte Carlo simulation frameworks to model cell population dynamics, one assuming stochastic reactions and the other deterministic reactions.

Limitations

The models may not account for all biological complexities and interactions present in natural systems.

Digital Object Identifier (DOI)

10.1186/1471-2105-12-301

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