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SIMULATION
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Experimental Design in Systems Biology, Based on Parameter Sensitivity Analysis Using a Monte Carlo Method: A Case Study for the TNF{alpha}-Mediated NF-{kappa} B Signal Transduction Pathway

Kwang-Hyun Cho

School of Electrical Engineering, University of Ulsan Ulsan, 680-749, Korea, ckh{at}mail.ulsan.ac.kr

Sung-Young Shin

School of Electrical Engineering, University of Ulsan Ulsan, 680-749, Korea

Walter Kolch

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

Olaf Wolkenhauer

Department of Computer Science, University of Rostock, Albert Einstein Str. 21 18059 Rostock, Germany, wolkenhauer{at}informatik.uni-rostock.de

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 TNF{alpha}-mediated NF-{kappa}B 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.

Key Words: Systems biology • experimental design • signal transduction pathway • mathematical modeling • parametric sensitivity • Monte Carlo method • TNF{alpha} • NF-{kappa}B

SIMULATION, Vol. 79, No. 12, 726-739 (2003)
DOI: 10.1177/0037549703040943
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