Boolean networks are coarse-grained models of the regulatory dynamics for survival and proliferation of a living cell. The dynamics is time- and state-discrete. The Boolean abstraction assumes digital information processing. The binary distinction of a low or a high concentration of each bio-molecule is sufficient to capture the dynamics. In the presentation, I offer an introduction to Boolean networks, examples of application to specific biological systems and the mathematical and computational treatment with state transition graphs.
Despite being a drastic simplification w.r.t. systems of coupled differential equations, analysis of specific Boolean networks --- rather than ensemble averages --- poses computational challenges. I present ongoing work on capturing long term dynamics by identifying fixed points and other invariant sets under stochastic asynchronous update.
Coffee and cookies will be served 15 minutes before the start of the seminar
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