Modelling the dynamics of signalling pathways

Author:

Sreenath Sree N.1,Cho Kwang-Hyun2,Wellstead Peter3

Affiliation:

1. Case Complex Systems Biology Center, Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH 44139, U.S.A.

2. Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea

3. The Hamilton Institute, National University of Ireland, Maynooth, Co. Kildare, Ireland

Abstract

In the present chapter we discuss methodologies for the modelling, calibration and validation of cellular signalling pathway dynamics. The discussion begins with the typical range of techniques for modelling that might be employed to go from the chemical kinetics to a mathematical model of biochemical pathways. In particular, we consider the decision-making processes involved in selecting the right mechanism and level of detail of representation of the biochemical interactions. These include the choice between (i) deterministic and stochastic chemical kinetics representations, (ii) discrete and continuous time models and (iii) representing continuous and discrete state processes. We then discuss the task of calibrating the models using information available in web-based databases. For situations in which the data are not available from existing sources we discuss model calibration based upon measured data and system identification methods. Such methods, together with mathematical modelling databases and computational tools, are often available in standard packages. We therefore make explicit mention of a range of popular and useful sites. As an example of the whole modelling and calibration process, we discuss a study of the cross-talk between the IL-1 (interleukin-1)-stimulated NF-κB (nuclear factor κB) pathway and the TGF-β (transforming growth factor β)-stimulated Smad2 pathway.

Publisher

Portland Press Ltd.

Subject

Molecular Biology,Biochemistry

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