Page "Gene regulatory network" Paragraph 23
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Genes in biological systems display a continuous range of activity levels and it has been argued that using a continuous representation captures several properties of gene regulatory networks not present in the Boolean model.
Formally most of these approaches are similar to an artificial neural network, as inputs to a node are summed up and the result serves as input to a sigmoid function, e. g., but proteins do often control gene expression in a synergistic, i. e. non-linear, way.
However there is now a continuous network model that allows grouping of inputs to a node thus realizing another level of regulation.
The same model has also been used to mimic the evolution of cellular differentiation and even multicellular morphogenesis.
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