My research will use integrative modeling of the interactions of the molecular elements to develop a more complete understanding of dynamic cellular signalling and information processing mechanisms. It will focus on information content of collected biological data, predictive power of developed models and gaining control over studied systems. This will be achieved via mathematically designed experimental protocols executed using microfluidic devices. A system of NF-kB signalling with TNF stimulation will serve as an initial model to develop theoretical and experimental tools. Methodology will be then utilized to better understand principles of LPS-IRF3 signalling.The complexity of biochemical systems causes informative experimentation to be a difficult task and makes mathematical modelling necessary to explain collected data. Unfortunately, selecting an appropriate model is usually problematic. Even measurements of all components of a dynamic biochemical system, do not allow for its reverse-engineering if observed only in a small number of experimental conditions. The only possibility to overcome the selectivity of available data is to perturb a system in a way that reveals desired information. The ability of microfluidics to generate spatial and temporal perturbations in extracellular environments provides a unique tool for execution of carefully designed stimuli.In my research, I will combine methods of experimental design with new possibilities of microfluidic devices in order to increase the predictive power of biochemical dynamical models and gain control over studied systems in vitro. The ability to control biological systems is essential to guide drug target selection and design new effective therapies.