My research relates to signal processing and model identification based on data obtained from biological experiments. However, it is not limited to identifying important biological parameters, but also incorporates understanding the relation of observed data and models to create a larger picture. This picture includes cell information processing, cognitive processes of a cell and a cell population, as well as the self-organization of a cell population. Just as the modeling of biological systems gradually increases our understanding of life, it also inspires engineering design. The behavior of each individual cell is programmed in biomolecular signaling networks, similarly as the behavior of a robot is described by a program, whose execution is supported by the robot hardware and its communication system. Therefore, studies of cells are more relevant for the development of swarm robotic systems than similar studies of multi-agent systems, in which the presence of the agent intelligence cannot be avoided. In this respect, my research leads both to the system understanding of biological cell populations and a new design in robotics.