Decoding complex biological networks - tracing essential and modulatory parameters in complex and simplified models of the cell cycle
2011

Understanding Cell Cycle Dynamics Through Mathematical Modeling

Sample size: 470 publication Evidence: moderate

Author Information

Author(s): Olivia Eriksson, Tom Andersson, Yishao Zhou, Jesper Tegnér

Primary Institution: Stockholm University and Karolinska Institutet

Hypothesis

Can a simplified mathematical model effectively characterize essential and modulatory parameters in the cell cycle?

Conclusion

The simplified model's parameter characterizations align well with the original model, providing useful predictions for parameter perturbations.

Supporting Evidence

  • The study identified essential and modulatory parameters through a sensitivity analysis of the original model.
  • Predictions from the simplified model were validated against the original model's outputs.
  • Most parameters were found to be either essential or modulatory based on the perturbation analysis.

Takeaway

This study looks at how cells divide and grow by using math to simplify complex processes, helping us understand which parts are most important.

Methodology

The study used sensitivity analysis and a simplified piecewise linear model to explore parameter effects on cell cycle dynamics.

Limitations

The hybrid model may not capture all behaviors of the original model, especially under large perturbations.

Digital Object Identifier (DOI)

10.1186/1752-0509-5-123

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