A Direct Derivative Method for Estimating Kinetic Parameters of Biological Networks
Challenged by strong nonlinearity of cellular network models,large uncertainty in model parameters,and noisy ex-perimental data,a new parameter estimation algorithm,direct derivative method (DDM),is presented in which the measurement data are firstly fitted with smoothing splines,and then the first-order derivative of state variables are evaluated and substituted into the model.Thus,a dynamic optimization problem is converted into a linear or nonlinear regression problem.There is no need to solve ordinary differential equations of the system models iteratively,the computational complexity is therefore reduced to a large extent.Taking the I κ B α -NF-κ B signal transduction pathways as an example,unknown parameters are estimated effectively using the proposed DDM algorithm,and various factors that affect the results are investigated.
JIA Jianfang YUE Hong
North University of China,Taiyuan 030051,P.R.China Department of Electrical and Electronic Engineering,University of Strathclyde,Glasgow G1 1QE,UK
国际会议
The 30th Chinese Control Conference(第三十届中国控制会议)
烟台
英文
1-6
2011-07-01（万方平台首次上网日期，不代表论文的发表时间）