Related Experiment Video
Updated: Feb 25, 2026
10:50
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
Published on: June 21, 2022
2.2K
How to deal with parameters for whole-cell modelling
Ann C Babtie1, Michael P H Stumpf2
1Department of Life Sciences, Imperial College London, London, UK a.babtie@imperial.ac.uk.
Journal of the Royal Society, Interface
|August 4, 2017
Summary
Creating realistic whole-cell models requires accurate molecular reaction rates. This study explores methods for estimating these parameters, finding that smaller parameter sets can explain cellular behavior, aiding model development.
Area of Science:
- Systems biology
- Computational biology
- Biophysics
Background:
- Whole-cell models are crucial for understanding cellular processes but require accurate kinetic and physiological parameters.
- Estimating hundreds or thousands of reaction rate parameters for these models is a significant challenge due to a lack of suitable frameworks.
Purpose of the Study:
- To review and compare existing approaches for estimating parameters in dynamical systems modeling of whole cells.
- To identify promising strategies for overcoming the limitations in current parameter estimation methodologies.
Main Methods:
- Comparative analysis of different parameter estimation and inference techniques.
- Exploration of methods for identifying and analyzing reduced parameter sets within large-scale dynamical systems.
Main Results:
- No single framework currently exists for reliably estimating all parameters in whole-cell models.
- Much of cellular behavior can be explained by smaller, identifiable parameter sets, even in large systems.
Conclusions:
- While complete parameter estimation remains challenging, focusing on reduced parameter sets offers a viable path forward.
- Identifying and analyzing these key parameter sets will be essential for developing and analyzing accurate whole-cell models.
