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Sealable Femtoliter Chamber Arrays for Cell-free Biology
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Stochastic modeling of cellular networks.

Jacob Stewart-Ornstein1, Hana El-Samad

  • 1Department of Biochemistry and Biophysics, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA.

Methods in Cell Biology
|April 10, 2012
PubMed
Summary
This summary is machine-generated.

Biological noise arises from random biochemical reactions, causing cell variability in mRNA and protein levels. This study models this stochasticity using jump Markov processes and the chemical master equation (CME).

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Area of Science:

  • Systems Biology
  • Biophysics
  • Computational Biology

Background:

  • Cellular processes exhibit inherent randomness due to molecular interactions.
  • This stochasticity, or biological noise, results in cell-to-cell variability in molecule levels.
  • This variability impacts crucial biological functions like antibiotic resistance and drug response.

Purpose of the Study:

  • To present a modeling framework for stochastic cellular behaviors.
  • To introduce the chemical master equation (CME) as a tool for analyzing biological noise.
  • To discuss computational methods for solving the CME.

Main Methods:

  • Modeling stochastic cellular dynamics using jump Markov processes.
  • Utilizing the chemical master equation (CME) to describe probability distributions.
  • Employing kinetic Monte Carlo simulations, including the stochastic simulation algorithm (SSA).
  • Applying method closure techniques like the linear noise approximation (LNA).

Main Results:

  • The study outlines the application of jump Markov processes and CME for modeling biological noise.
  • It details simulation techniques (SSA) and analytical approximations (LNA) for solving the CME.
  • The presented methods allow for the quantitative analysis of cell-to-cell variability.

Conclusions:

  • Stochasticity is a fundamental aspect of biological systems with significant functional consequences.
  • Jump Markov processes and the CME provide a robust framework for modeling cellular noise.
  • Computational methods like SSA and LNA are essential for analyzing these stochastic models.