Gene expression is often maintained by a complex network of
cross-regulatory interactions. In this talk I will focus on the
segment polarity genes of Drosophila melanogaster, and the network
of interactions determining the stability of their expression. I
will present a Boolean representation of this network that assumes
that genes and proteins are either ON or OFF, and their interactions
can be formulated as logical functions. This simple model is able
to reproduce the wild type expression obtained for gene mutation
experiments. In addition, the Boolean representation allows for a more
complete analysis of the possible steady states as experiments, and for
a better identification of the initial conditions that lead to certain
steady states. I propose this type of analysis as a first, qualitative
step in understanding complex networks. The success of a Boolean
representation strongly suggests that the topology of the network
is correctly taken into account, and a more quantitative approach
can be used.
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