Elucidating the topology and dynamics of biological networks from
experimental data is a central goal of systems biology. Recently
algebraic models have been introduced as a new framework for modeling
and analyzing biological networks as multi-states systems,
generalizing Boolean networks. Within this framework, using tools from
computational algebra and algebraic geometry, algorithmic methods that
find and present the model space have been developed, and the class of
nested canalyzing models have been characterized. Furthermore,
methods for analyzing the dynamics of monomial models have been
developed. The algebraic framework as well as some of the mentioned
methods will be presented in this talk.