Our work is focused on the analysis of information processing capabilities of biological systems from both, syntetic and analytic aspect. Computational part of the project addresses the questions, such us how to design a set of biological modules that are functionally complete, robust and may be used in a scalable manner. In order to do this efficiently our group is developing computational methods for efficient modelling, simulation, analysis and design of biological systems, with a special focus on gene regulatory networks with complex regulation, such as competitive regulation with multiple transcription factor binding sites.

One hypothesis about the origins and evolution of coordinated animal movements is that they may serve as a defensive mechanism against predation. Computational studies of the possible evolution of coordinated movement in prey typically concentrate on predators with simple attack tactics. Numerous studies, however, suggest that to overcome the apparent defensive mechanisms which grouping and coordinated movement may provide to prey, predators in nature appear to use elaborate target selection and pursuit/hunting tactics. We concentrate on the development of artificial life-like evolutionary models based on fuzzy logic in order to study the evolution of complex target selection and pursuit tactics, as well as the evolution of non-trivial coordinated movement. Collective behaviour is a research field with a very wide interdisciplinary appeal, studies showed that it can aid gaining a better insight into the behaviour of animals, start and stop traffic jams, crowd behaviour at events such as football games or music concerts, and even in the bureaucracy of the European Union. Finally yet importantly comparable patterns were observed in cancerous cells.