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

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.


Published in:
International Journal of Robust and Nonlinear Control - Special Issue on System Identification for Biological Systems, 22, 10, 1140-1156
Year:
2012
Laboratories:




 Record created 2017-01-10, last modified 2020-10-25


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