Complex dynamical biomolecular systems govern virtually all biological processes on developmental and physiological time scales. A paramount problem is to understand how structural and dynamical properties of such systems affect their roles in cellular function and dysfunction. Our group has developed network inference approaches by integrating the information from multiple types of measurement data using a variety of modeling formalisms.  Such models can be used for developing optimal therapeutic strategies intended to control system behavior in disease.

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