<i>φ</i>-evo: A program to evolve phenotypic models of biological networks - Fig 4

<p>Pareto evolution of embryonic patterning (A) Schematic representation of the problem: we model embryonic patterning as an antero posterior sequence of genes at different positions (B) Fitness definition, where <i>p</i>(<i>i</i>; <i>x</i>) represents the relative fraction of gene <i>i</i> expressed at position <i>x</i>. <i>F</i>₁ increases with the number of genes expressed within the embryo, while <i>F</i>₂ increases with the number of genes expressed locally at <i>x</i>. See [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006244#pcbi.1006244.ref009" target="_blank">9</a>] for more details on the two fitnesses (C) Pareto fronts for a single evolutionary simulation at different generations (warmer colours correspond to later generations) aiming at maximizing <i>F</i>₁ and minimizing <i>F</i>₂ simultaneously. Inset corresponds to the evolutionary trajectory studied in panel E (D) Changes of functions <i>F</i>₁ and <i>F</i>₂ for random mutations within a network population (E) An evolutionary trajectory leading to the definition of a new Pareto front, from 3 to 4 domains. Only the local probability profiles for the steady states of the networks are displayed.