The nature of statistical learning theory
The nature of statistical learning theory
Linear Modeling of Genetic Networks from Experimental Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
HSCC'05 Proceedings of the 8th international conference on Hybrid Systems: computation and control
Comparison of four procedures for the identification of hybrid systems
HSCC'05 Proceedings of the 8th international conference on Hybrid Systems: computation and control
A clustering technique for the identification of piecewise affine systems
Automatica (Journal of IFAC)
Brief paper: A mathematical framework for the control of piecewise-affine models of gene networks
Automatica (Journal of IFAC)
HSCC '08 Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control
Simulation of stochastic hybrid systems with switching and reflecting boundaries
Proceedings of the 40th Conference on Winter Simulation
Parameters estimation of systems with delayed and structured entries
Automatica (Journal of IFAC)
Local Identification of Piecewise Deterministic Models of Genetic Networks
HSCC '09 Proceedings of the 12th International Conference on Hybrid Systems: Computation and Control
Parameter Synthesis in Nonlinear Dynamical Systems: Application to Systems Biology
RECOMB 2'09 Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology
Switch detection in genetic regulatory networks
HSCC'07 Proceedings of the 10th international conference on Hybrid systems: computation and control
Algebraic systems biology: theses and hypotheses
AB'07 Proceedings of the 2nd international conference on Algebraic biology
The Knowledge Engineering Review
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Recent advances of experimental techniques in biology have led to the production of enormous amounts of data on the dynamics of genetic regulatory networks. In this paper, we present an approach for the identification of PieceWise-Affine (PWA) models of genetic regulatory networks from experimental data, focusing on the reconstruction of switching thresholds associated with regulatory interactions. In particular, our method takes into account geometric constraints specific to models of genetic regulatory networks. We show the feasibility of our approach by the reconstruction of switching thresholds in a PWA model of the carbon starvation response in the bacterium Escherichia coli.