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Related Concept Videos

Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
Cooperative Allosteric Transitions01:58

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Reaction Mechanisms: The Steady-State Approximation

The steady-state approximation, also referred to as the quasi-steady-state approximation to differentiate it from a true steady state, is a widely used method for simplifying calculations in complex reaction mechanisms. This approach is particularly useful when dealing with multi-step reactions that involve reverse reactions or several steps, which can significantly increase mathematical complexity and make the reactions nearly unsolvable analytically.The steady-state approximation operates on...
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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...

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Model reduction, coherence, and information transfer in stochastic biochemical systems.

Juan David Marmolejo-Lozano1, Nikola Popović2,3, Ramon Grima1

  • 1University of Edinburgh, School of Biological Sciences, Edinburgh, United Kingdom.

Physical Review. E
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Summary

Simplified models accurately capture molecular counts but often fail to accurately estimate coherence and mutual information (MI) rates in biochemical networks due to discrepancies in frequency-resolved noise propagation.

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Area of Science:

  • Biophysics
  • Systems Biology
  • Biochemical Kinetics

Background:

  • Stochastic models are crucial for analyzing noise propagation and information transmission in biochemical reaction networks.
  • Coherence and mutual information (MI) rate are key metrics for quantifying these processes.
  • Reduced models are commonly used approximations of complex biochemical systems.

Purpose of the Study:

  • To challenge the assumption that simplified models accurately approximate coherence and MI rates in biochemical networks.
  • To investigate the discrepancies in frequency-resolved noise propagation between full and reduced models.
  • To identify the factors contributing to these inaccuracies in simplified models.

Main Methods:

  • Analysis of frequency-resolved noise propagation in biochemical reaction networks.
  • Comparison of coherence spectra and mutual information (MI) rates between full and reduced models.
  • Investigation of model reduction methods and their impact on statistical properties.

Main Results:

  • Reduced models accurately reproduce low-order statistics of molecular counts.
  • Significant discrepancies are observed in coherence spectra at intermediate and high frequencies.
  • These discrepancies lead to substantial inaccuracies in estimated mutual information (MI) rates.

Conclusions:

  • Simplified stochastic models may not reliably estimate coherence and mutual information (MI) rates, despite accurately capturing molecular counts.
  • The accuracy of reduced models depends on network structure, reduction method, and asymptotic limits.
  • Careful consideration is needed when using simplified models for quantifying information flow in biological systems.