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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Implementation of dynamic Bayesian decision making by intracellular kinetics.

Tetsuya J Kobayashi1

  • 1Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba Meguro-ku, Tokyo 153-8505, Japan. tetsuya@mail.crmind.net

Physical Review Letters
|September 28, 2010
PubMed
Summary

Cells make dynamic decisions in changing environments using intracellular kinetics. A dual positive feedback structure enables efficient Bayesian decision-making, suppressing noise for robust cellular responses.

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Area of Science:

  • Cellular biology
  • Systems biology
  • Computational neuroscience

Background:

  • Cells operate in noisy, dynamic environments requiring efficient decision-making.
  • Intracellular kinetics are crucial for implementing dynamic decision processes.

Purpose of the Study:

  • To demonstrate how intracellular kinetics can implement dynamic Bayesian decision-making.
  • To identify key features of intracellular kinetics that enhance decision efficiency and noise suppression.

Main Methods:

  • Application of sequential inference theory.
  • Analysis of intracellular kinetics with dual positive feedback structures.
  • Investigation of input sensitivity properties.

Main Results:

  • Dynamic Bayesian decision-making is achievable with a dual positive feedback intracellular kinetic structure.
  • A combination of linear and nonlinear sensitivities enhances decision efficiency.
  • State-dependent sensitivity changes effectively suppress noisy cellular responses.

Conclusions:

  • Intracellular kinetics can implement efficient and robust cellular decision-making.
  • Key statistical principles include log-likelihood-dependent information quantification and uncertainty-dependent sensitivity control.