Mathematical models of GRNs have been developed to allow predictions of the models to be tested. Various modeling techniques have been used, including boolean networks, Petri nets, Bayesian networks, and sets of differential equations. Conversely, techniques have been proposed for generating models of GRNs that best explain a set of time series observations.
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The following example illustrates how a Boolean network can model a GRN together with its gene products (the outputs) and the substances from the environment that affect it (the inputs). Stuart Kauffman was amongst the first biologists to use the metaphor of Boolean networks to model genetic regulatory networks.
Example: Boolean network
The validity of the model can be tested by comparing simulation results with time series observations.