Identification of quadratic nonlinear models oriented to genetic network analysis

F Amato; M Bansal; C Cosentino; W Curatola; D Di Bernardo

doi:10.1109/IEMBS.2005.1615759

Identification of quadratic nonlinear models oriented to genetic network analysis

Conf Proc IEEE Eng Med Biol Soc. 2005:2005:5615-8. doi: 10.1109/IEMBS.2005.1615759.

Authors

F Amato¹, M Bansal, C Cosentino, W Curatola, D Di Bernardo

Affiliation

¹ School of Computer and Biomedical Engineering, Università degli Studi Magna Graecia di Catanzaro, Campus di Germaneto, Viale Europa, 88100 Catanzaro, Italy; amato@unicz.it.

PMID: 17281529
DOI: 10.1109/IEMBS.2005.1615759

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.