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Sensitivity analysis and parameter estimation of signal transduction pathways model

Jia, J.F. and Yue, H. (2009) Sensitivity analysis and parameter estimation of signal transduction pathways model. In: 7th Asian Control Conference, 2009 (ASCC 2009), 2009-08-27 - 2009-08-29.

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Abstract

Due to the high nonlinearity in system models, the large number of kinetics parameters involved, the inadequate measurement data in experiments and the noise pollution, etc., parameter estimation is therefore a challenging problem in systems biology. In this work, sensitivity analysis of model output with respect to model parameters is evaluated using Latin hypercube sampling method. Then, a new objective function is proposed based on the probability density function (PDF) of the system output, and particle swarm optimization is used to optimize the objective function through particles' cooperation and evolution. Taking NF-kappaB signal pathways model as an example, this method is applied to rank importance of parameters and to estimate the unknown sensitive parameters for complex signal transduction pathways model. The simulation results show the effectiveness of this new algorithm.

Item type: Conference or Workshop Item (Paper)
ID code: 14725
Keywords: biological system modeling, kinetic theory, noise measurement, biology computing, parameter estimation, particle swarm optimisation, probability, sensitivity analysis, Electrical engineering. Electronics Nuclear engineering
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
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Depositing user: Strathprints Administrator
Date Deposited: 09 May 2011 12:14
Last modified: 17 Jul 2013 15:45
URI: http://strathprints.strath.ac.uk/id/eprint/14725

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