【摘 要】
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Biological processes are very complex; involving many components with intricate interactions and also influenced by environment.Modelling such processes int
【机 构】
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Industrial & Financial Mathematics Research Division
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Biological processes are very complex; involving many components with intricate interactions and also influenced by environment.Modelling such processes into mathematical equations often leads to a very large nonlinear differential equation system with many parameters.Some or even all of these parameters might have to be estimated from noisy experimental data.Although some methods are available,the task of estimating parameters remains a challenging task,especially due to the high number of parameter to estimate,noisy data,and limited number of measurable components.In this work,we propose an alternative method to estimate the parameters based on the ensemble Kalman filter.To test the performance,the method is applied to estimate parameters in the heat shock response model.The results show a good agreement.
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