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We are trying to reproduce Turing patterns using a genetic network. These spatial structures could in principle be generated by perturbing equilibrium configurations by the action of diffusion. They have been extensively studied and reproduced in the context of chemical reactions. In biological systems they are thought to play an important role in some morphogenetic processes.

Some spatial and temporal structures seem to match and resemble those predicted by Turing, such as the ones observed in the organization of trychomes and trychoblasts in Arabidopsis thaliana’s leafs or root as well as in coloring patterns in plants and animals. Yet it is still controversial whether they are actually Turing patterns, since the underlying genetic network is not completely understood.

Although many mathematical models have been built based on these ideas in order to reproduce what is observed in biological systems, the identification of the actual substances that create the patterns (morphogenes) is still not clear. We propose a different approach, namely, to implement a genetic network of the activator-inhibitor type in order to recover Turing patterns in bacterial colonies. We believe that the standard diffusion might be substituted by other effective intercellular communication mechanisms. If successful, our construction will allow us to introduce the notion of “effective morphogenes”.