Model reduction and parameter estimation of non-linear dynamical biochemical reaction networks
Xiaodian Sun1, Mario Medvedovic2
1Department of Environmental Health, Laboratory for Statistical Genomics and Systems Biology, University of Cincinnati College of Medicine, 3223 Eden Ave. ML56, Cincinnati, OH 45267-0056, USA. sunxd@uc.edu.
IET Systems Biology
|January 28, 2016
Summary
This study introduces Rao-Blackwellised particle filters decomposition methods to improve parameter estimation in complex dynamic systems. The approach reduces model dimensions and enhances accuracy for large-scale biological network analysis.
Area of Science:
- Computational Biology
- Systems Biology
- Statistical Inference
Background:
- Parameter estimation in high-dimensional dynamic systems faces the
- large p small n
- problem, limiting accuracy and scalability.
Purpose of the Study:
- To develop a novel method for dimension reduction and improved parameter estimation in complex dynamic systems.
- To address the limitations of current statistical models in high-dimensional biological networks.
Main Methods:
- Incorporation of prior knowledge (parameters, structure) into dynamic models.
- Decomposition of dynamic models into modular subnetworks.
- Application of different estimation approaches to subnetworks, termed Rao-Blackwellised particle filters decomposition.
Main Results:
- Demonstrated performance on synthetic repressilator model data.
- Validated on experimental JAK-STAT pathway data.
- Method shows potential for extension to large-scale dynamic systems.
Conclusions:
- Rao-Blackwellised particle filters decomposition effectively reduces dimensionality and enhances parameter estimation accuracy.
- The method offers a scalable solution for analyzing complex biological dynamic systems.
- This approach is adaptable for various large-scale dynamic modeling applications.
Related Concept Videos
02:31Multi-Step Reactions
9.0K
Chemical reactions often occur in a stepwise fashion involving two or more distinct reactions taking place in a sequence. A balanced equation indicates the reacting species and the product species, but it reveals no details about how the reaction occurs at the molecular level. The reaction mechanism (or reaction path) provides details regarding the precise, step-by-step process by which a reaction occurs. Each of the steps in a reaction mechanism is called an elementary reaction. These...
9.0K
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
394
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...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
394
01:13Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model
389
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
389
01:29Reaction Mechanisms: Rate-limiting Step Approximation
64
The rate-determining step, or RDS, in a chemical reaction is the slowest step that determines the overall reaction rate. It is identified by using the observed rate law and typically involves approximation methods like the RDS approximation or the steady-state approximation.In the RDS approximation, also known as the rate-limiting-step or equilibrium approximation, the reaction mechanism consists of one or more reversible reactions near equilibrium, followed by a slower RDS, and then one or...
64
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
321
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...
321
01:06Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
310
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
310