Modeling and analysis of integrated metabolic, proteomic and genetic regulatory networs

Recent advances in experimental biology enable for the first time the systematic reconstruction of large cellular signaling and regulatory networks. This prompted the birth of `systems biology', which aims to understand the emergence of thelarge scale functional properties of cells from the complex interactions between their molecular components. Achieving this aim requires intensive collaboration between biologists and mathematicians. So far, the mathematical study of complex cellular networks has mainly focused on their topological characterization and evolutionary origin. However, in a separate development, since around 2000 the disordered systems community has been generating powerful new mathematical techniques with which to analyze and solve stochastic processes on complex random graphs in physics and computer science. The aim of this project is to investigate and harvest the potential of transferring these new techniques (in suitably adapted form) to the field of integrated metabolic, proteomic and genetic regulatory networks.