DocumentCode
1582809
Title
Identification of Quadratic Nonlinear Models Oriented to Genetic Network Analysis
Author
Amato, F. ; Bansal, M. ; Cosentino, C. ; Curatola, W. ; Di Bernardo, D.
Author_Institution
Sch. of Comput. & Biomed. Eng., Univ. degli Studi Magna Gracia di Catanzaro
fYear
2005
fDate
6/27/1905 12:00:00 AM
Firstpage
5615
Lastpage
5618
Abstract
The goal of this paper is to provide a novel procedure for the identification of nonlinear models which exhibit a quadratic dependence on the state variables. These models turn out to be very useful for the description of a large class of biochemical processes with particular reference to the genetic networks regulating the cell cycle. The proposed approach is validated through extensive computer simulations on randomly generated systems
Keywords
biochemistry; cellular biophysics; genetics; molecular biophysics; physiological models; biochemical processes; cell cycle; genetic network analysis; quadratic nonlinear models; state variables; Biological system modeling; Cellular networks; Computer networks; Computer simulation; Differential equations; Genetic expression; Limit-cycles; Mathematical model; Network topology; Proteins;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location
Shanghai
Print_ISBN
0-7803-8741-4
Type
conf
DOI
10.1109/IEMBS.2005.1615759
Filename
1615759
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