DocumentCode
232627
Title
Least squares identification method for differential equations of gene regulatory networks
Author
Gao Yanpu ; Wang Dongqing
Author_Institution
Coll. of Autom. Eng., Qingdao Univ., Qingdao, China
fYear
2014
fDate
28-30 July 2014
Firstpage
6764
Lastpage
6768
Abstract
This paper transforms a differential equation model of a gene regulatory network into a discrete equation by using the explicit Euler method. A recursive least squares algorithm is presented to generate the parameter estimates by replacing the unknown true outputs with their estimates. The simulation results indicate that the proposed algorithm is effective and is of a high estimation accuracy.
Keywords
differential equations; genetics; least squares approximations; network theory (graphs); parameter estimation; Euler method; GRN; differential equations; discrete equation; genetic regulatory networks; least square identification method; parameter estimates; Computational modeling; Differential equations; Equations; Least squares approximations; Mathematical model; Parameter estimation; Vectors; Differential equation; Gene regulatory networks; Least squares; Parameter estimation; System identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2014 33rd Chinese
Conference_Location
Nanjing
Type
conf
DOI
10.1109/ChiCC.2014.6896113
Filename
6896113
Link To Document