Marc A. Schaub, Thomas A. Henzinger, and Jasmin Fisher
A central goal of Systems Biology is to model and analyze biological signaling pathways that interact with one another to form complex networks. Here we introduce qualitative networks, an extension of boolean networks. Within this framework, we use formal verification methods to check whether a model is consistent with the laboratory experimental observations on which it is based. If the model does not conform to the data, we suggest a revised model, and the new hypotheses are tested in-silico.
We consider networks in which elements range over a small finite domain, allowing more flexibility than boolean values, and add target functions that allow to model a rich set of behaviors. We propose a symbolic algorithm for analyzing the steady state of these networks, allowing us to scale up to a system consisting of 144 elements and state spaces of approximately 1086 states. We illustrate the usefulness of this approach through a model of the interaction between the Notch and the Wnt signaling pathways in mammalian skin, and its extensive analysis.
BMC Systems Biology 1:4, 2007.