Experimental Design in Systems Biology, Based on Parameter Sensitivity Analysis Using a Monte Carlo Method: A Case Study for the TNFα-Mediated NF-κ B Signal Transduction Pathway
Abstract
Mathematical modeling and dynamic simulation of signal transduction pathways is a central theme in systems biology and is increasingly attracting attention in the postgenomic era. The estimation of model parameters from experimental data remains a bottleneck for a major breakthrough in this area. This study’s aim is to introduce a new strategy for experimental design based on parameter sensitivity analysis. The approach identifies key parameters/variables in a signal transduction pathway model and can thereby provide experimental biologists with guidance on which proteins to consider for measurement. The article focuses on applying this approach to the TNFα-mediated NF-κB pathway, which plays an important role in immunity and inflammation and in the control of cell proliferation, differentiation, and apoptosis. A mathematical model of this pathway is proposed, and the sensitivity analysis of model parameters is illustrated for this model by employing the Monte Carlo method over a broad range of parameter values.
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Collectively fitting parameters by optimizing agreement between model and available data often yields large parameter uncertainties.
“On the other hand, collectively fitting parameters [11,12] by optimizing the agreement between the model and available data often yields large parameter uncertainties [13–15].”
From Universally Sloppy Parameter Sensitivities in Systems Biology Models (2007) · cites this paper as [15]
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- Authors
- Cho, K.-H., Shin, S.-Y., Kolch, W., & Wolkenhauer, O.
- Affiliations
- University of Ulsan (KR)
- Beatson Institute for Cancer Research, Cancer Research UK, Beatson Laboratories, Switchback Road, Glasgow, G61 1BD, United Kingdom, Institute of Biomedical and Life Sciences, University of Glasgow University Avenue, Glasgow, G12 8QQ, United Kingdom
- Department of Computer Science, University of Rostock, Albert Einstein Str. 21 18059 Rostock, Germany,
- Corresponding author
- Cho, Kwang-Hyun
- Venue
- SIMULATION
- Publisher
- SAGE Publications
- Published
- 2003-12
- Volume
- 79
- Issue
- 12
- Pages
- 726-739
- ISSN
- 0037-5497 (ISSN-L)
- 1741-3133
- OpenAlex
- W2166565152
- Cited by
- 172
- References
- 31
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 5 · 2020: 2 · 2019: 6 · 2018: 4 · 2016: 5 · 2015: 12 · 2014: 10 · 2013: 18 · 2012: 11
- FWCI
- 2.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- SIMULATION (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › NF-κB Signaling Pathways
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Keywords
- experimental design, parameter sensitivity analysis, Monte Carlo methods, signaling pathways, TNF-α, NF-κB signaling, parameter estimation, model reduction, inflammation, immunity
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