Title: Structure of deviations from optimality in biological systems
Authors: Alfonso Pérez-Escudero, Marta Rivera-Alba and Gonzalo G. de Polavieja
Abstract:Optimization theory has been used to analyze evolutionary adaptation. This theory has explained many features of biological systems, from the genetic code to animal behaviour. However, these systems show important deviations from optimality. Typically, these deviations are large in some particular components of the system, while others seem to be almost optimal. Here we test whether important factors in evolution like stochasticity or finite time can predict the structure of deviations from optimality. These factors are shown to imply a simple rule: the most likely deviations are in those components with less impact on the indirect measure of fitness chosen as objective for the optimization. To show the generality of this rule, we tested it in two very different systems. In Caenorhabditis elegans, this rule is shown to succesfully explain the experimental structure of deviations of the position of neurons from the configuration of minimal wiring cost. In Escherichia coli, the probabilistic rule correctly obtains the structure of the experimental deviations of metabolic fluxes from the configuration that maximizes biomass production. This approach is proposed to provide a more realistic and predictive framework than optimization theory while using no extra parameters. Thus it can be used to rigorously test and refine hypothesis about which constraints have shaped biological structures in evolution.
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