Modeling genetic networks and their evolution: A complex dynamical systemsperspective

After finishing the sequence of the human genome, a functional understandin g of genome dynamics is the next major step on the agenda of the bioscience s. New approaches, such as microarray techniques, and new methods of bioinf ormatics provide powerful tools aiming in this direction. In the last few y ears, important parts of genome organization and dynamics in a number of mo del organisms have been determined. However, an integrated view of gene reg ulation on a genomic scale is still lacking. Here, genome function is discu ssed from a complex dynamical systems perspective: which dynamical properti es can a large genomic system exhibit in principle, given the local mechani sms governing the small subsystems that we know today? Models of artificial genetic networks are used to explore dynamical principles and possible eme rgent dynamical phenomena in networks of genetic switches. One observes evo lution of robustness and dynamical self-organization in large networks of a rtificial regulators that are based on the dynamic mechanism of transcripti onal regulators as observed in biological gene regulation. Possible biologi cal observables and ways of experimental testing of global phenomena in gen ome function and dynamics are discussed. Models of artificial genetic netwo rks provide a tool to address questions in genome dynamics and their evolut ion and allow simulation studies in evolutionary genomics.