Breschine Cummins, Marcio Gameiro, Konstantin Mischaikow, Tomas Gedeon
Autonomous oscillators in systems biology are often mathematically expressed as regulatory network models. These models are interrogated to predict oscillator behavior under various environmental conditions. The potential suite of dynamical behaviors arising from a regulatory network model is rich and varied, as one might expect of a complex system. Therefore, a mathematical model has the capability to predict previously unobserved biological oscillator behavior that arises under untested conditions. We present a computational method that describes the full suite of dynamical behaviors of a network model, enabling both mechanistic understanding of experimental observations and prediction of unexpected dynamics. These ideas are presented through example network models, including some relevant to the yeast cell cycle.