Patterning by genetic networks

We consider here the morphogenesis (pattern formation) problem for some genetic network models. First, we show that any given spatio-temporal pattern can be generated by a genetic network involving a sufficiently large number of genes. Moreover, patterning process can be performed by an effective algorithm. We also show that Turingʹs or Meinhardtʹs type reaction-diffusion models can be approximated by genetic networks. These results exploit the fundamental fact that the genes form functional units and are organized in blocks. Due to this modular organization, the genes always are capable to construct any new patterns and even any time sequences of new patterns from old patterns. Computer simulations illustrate some analytical results.