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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
Published on: December 7, 2021
Relating network rigidity, time scale hierarchies, and expression noise in gene networks
Ovidiu Radulescu1, Guilherme C P Innocentini, José Eduardo M Hornos
1Laboratoire de Dynamique des Interactions Membranaires Normales et Pathologiques, CNRS-UMR 5235, CC107, Université Montpellier II, Place Eugène Bataillon, 34095 Montpellier Cedex 5, France.
Summary
Fluctuation-dissipation theorems link system noise to macroscopic responses. This study relates gene expression noise to gene network topology and timescales using a Fokker-Planck equation.
Area of Science:
- Systems Biology
- Statistical Physics
Background:
- Fluctuation-dissipation theorems connect macroscopic system responses to internal noise characteristics.
- Gene networks exhibit feedback control, influencing their "network rigidity" against external perturbations.
Purpose of the Study:
- To develop an effective Fokker-Planck equation for gene networks.
- To link gene expression noise to network topology and timescales.
- To explore noise buffering mechanisms under different time hierarchies.
Main Methods:
- Formulation of an effective Fokker-Planck equation.
- Analysis of gene networks with varying topology and timescales.
- Distinction between normal and inverted time hierarchy scenarios.
Main Results:
- The proposed equation relates gene expression noise to network topology and timescales.
- Noise buffering by network feedback is observed under normal time hierarchies.
- Noise can be independent of topology in inverted time hierarchies.
Conclusions:
- Gene network feedback and timescale hierarchy significantly influence gene expression noise.
- The Fokker-Planck equation provides a framework for understanding noise regulation in gene networks.
- Understanding these dynamics is crucial for predicting cellular behavior and designing synthetic gene circuits.
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