DocumentCode :
2933177
Title :
Parameter estimation method for improper fractional models and its application to molecular biological systems
Author :
Tian, Lig-Ping ; Liu, Lizhi ; Wu, Fang-Xiang
Author_Institution :
Sch. of Inf., Beijing Wuzi Univ., Beijing, China
fYear :
2010
fDate :
Aug. 31 2010-Sept. 4 2010
Firstpage :
1477
Lastpage :
1480
Abstract :
Derived from biochemical principles, molecular biological systems can be described by a group of differential equations. Generally these differential equations contain fractional functions plus polynomials (which we call improper fractional model) as reaction rates. As a result, molecular biological systems are nonlinear in both parameters and states. It is well known that it is challenging to estimate parameters nonlinear in a model. However, in fractional functions both the denominator and numerator are linear in the parameters while polynomials are also linear in parameters. Based on this observation, we develop an iterative linear least squares method for estimating parameters in biological systems modeled by improper fractional functions. The basic idea is to transfer optimizing a nonlinear least squares objective function into iteratively solving a sequence of linear least squares problems. The developed method is applied to the estimation of parameters in a metabolism system. The simulation results show the superior performance of the proposed method for estimating parameters in such molecular biological systems.
Keywords :
biochemistry; iterative methods; least squares approximations; molecular biophysics; nonlinear estimation; parameter estimation; polynomials; biochemical principles; differential equations; fractional models; iterative solving; linear least squares; metabolism system; molecular biological systems; nonlinear least squares; parameter estimation method; polynomials; Biological system modeling; Biological systems; Estimation; Least squares methods; Mathematical model; Parameter estimation; Polynomials; improper fractional model (IFM); iterative linear least squares algorithm; metabolism systems; molecular biological systems; parameter estimation; Adenosine Diphosphate; Adenosine Triphosphate; Animals; Computer Simulation; Energy Metabolism; Glucose; Glycolysis; Humans; Models, Biological; Pyruvic Acid; Signal Transduction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4123-5
Type :
conf
DOI :
10.1109/IEMBS.2010.5626849
Filename :
5626849
Link To Document :
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