Invalidation of the structure of genetic network dynamics: a geometric approach

Ricardo Porreca (1) , Eugenio Cinquemani (2) , John Lygeros (1) , Giancarlo Ferrari-Trecate (3)

1 IFA - Institut für Automatik - Automatic Control Laboratory
2 IBIS - Modeling, simulation, measurement, and control of bacterial regulatory networks
3 DIS - Dipartimento di Informatica e Sistemistica

This work concerns the identification of the structure of a genetic network model from measurements of gene product concentrations and synthesis rates. In earlier work, we developed a data preprocessing algorithm that is able to reject many hypotheses on the network structure by testing certain monotonicity properties for a wide family of network models. Here, we develop a geometric interpretation of the method. Then, for a relevant subclass of genetic network models, we extend our approach to the combined testing of monotonicity and convexity-like properties associated with the network structures. The theoretical aspects and practical performance of the enhanced methods are illustrated by way of numerical results.

Mots clés: Keywords: systems biology; identification; quasi-convexity; unate functions; sigmoidal activation functions

Domaines: Génétique

Ricardo Porreca, Eugenio Cinquemani, John Lygeros, Giancarlo Ferrari-Trecate. Invalidation of the structure of genetic network dynamics: a geometric approach. International Journal of Robust and Nonlinear Control, 2012, Special Issue: System Identification for Biological Systems, 22 (10), pp.1140-1156. ⟨10.1002/rnc.2799⟩. ⟨hal-00762592⟩