Computational study of noise in a large signal transduction network
2011

Studying Noise in a Biochemical Network

Sample size: 300 publication Evidence: moderate

Author Information

Author(s): Intosalmi Jukka, Manninen Tiina, Ruohonen Keijo, Linne Marja-Leena

Primary Institution: Tampere University of Technology

Hypothesis

The role of noise in biochemical systems can be quantitatively analyzed through simulations.

Conclusion

Noise plays an important role in biochemical systems, and its properties can be studied by simulating the system in different cellular volumes.

Supporting Evidence

  • Noise can make biochemical systems more robust to external changes.
  • The strength of noise decreases as the volume of the system increases.
  • Different species in the network exhibit varying levels of noise.
  • Parallel computing techniques allowed for efficient simulation of large networks.

Takeaway

This study looks at how noise affects chemical reactions in cells, showing that noise can actually help the system work better.

Methodology

The study used the Gillespie stochastic simulation algorithm to simulate a large biochemical network in 300 different cellular volumes.

Limitations

The study focuses on a specific biochemical network and may not generalize to all systems.

Digital Object Identifier (DOI)

10.1186/1471-2105-12-252

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