Abstract
SUMMARYThis 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 convexityâlike properties associated with the network structures. The theoretical aspects and practical performance of the enhanced methods are illustrated by way of numerical results. Copyright Š 2012 John Wiley & Sons, Ltd.
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