There is a growing demand for methods that can make predictions of qualitative properties of the dynamics of molecular interaction networks, that is, properties that are invariant for a range of reaction mechanisms and values of kinetic constants. On the one hand, precise and quantitative information on reaction mechanisms and kinetic constants is not available for most networks of biological interest. On the other hand, in many situations predictions of qualitative rather than quantitative dynamical properties are appropriate for gaining an understanding of the functioning of a molecular interaction network. This chapter discusses three examples of qualitative approaches for the analysis of genetic regulatory networks, allowing qualitative dynamical properties to be inferred from currently-available incomplete and non-quantitative data. The approaches are based on different formalisms, namely discrete abstractions of differential equations, Boolean networks, and graphs. We illustrate the approaches by means of a simple two-gene network and give an example of their application to real biological systems.

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