One object of systems biology is to develop the mathematical models of biochemical networks in cell and to analysis the system dynamic properties based on these models as well as to predict the system output. However, strong nonlinearity, complexity, noisy and incomplete measurements make the parameter estimation more difficult. In this paper, Unscented Kalman filter was proposed to estimate the unknown parameters and the unobservable state variables simultaneously. TNFα mediated NF-κB signal transduction pathway was taken as an example to illustrate the effectiveness of the method. Simulation results are encouraging and show that both parameters and unobservable state variables can be estimated well.
|Number of pages||13|
|Journal||Acta Biophysica Sinica|
|Publication status||Published - 2007|
- systems biology
- biochemical networks
- unscented Kalman filter