Alessandro Ferrarini Department of Evolutionary and Functional Biology, University of Parma, Via G. Saragat 4, I-43100 Parma, Italy Network Biology ISSN 2220-8879 http://www.iaees.org/publications/journals/nb/online-version.asp 2015 5 1 34 42 International Academy of Ecology and Environmental Sciences Hong Kong 27 October 2014 30 November 2014 1 March 2015 Evolutionary Network Control genetic algorithms global dynamics nonlinear networks predator-prey model sensitivity analysis stochastic simulations The proof of our understanding of ecological and biological systems is measured by our skill to rule them, i.e. to channelize them towards a desired state. Control is a cardinal issue in most complex systems, but because a general theory to apply it in a quantitative manner has been absent so far, little was known about how we can rule weighted, directed networks that represent the most common configuration of real systems. To this purpose, Evolutionary Network Control (ENC) has been developed as a theoretical and methodological framework aimed to the control of ecological and biological networks by coupling network dynamics and evolutionary modelling. ENC is a tools to address controllability for arbitrary network topologies and sizes. ENC has proven to cover several topics of network control, e.g. a) the global control from inside and b) from outside, c) the local (step-by-step) control, and the computation of: d) control success, e) feasibility, and f) degree of uncertainty. Taken together, these results indicate that many aspects of controllability can be explored exactly and analytically for arbitrary networks, opening new avenues to deepening our understanding of complex systems. As yet, I have applied ENC only to linear ecological and biological networks. In this work, I show that ENC also holds for any kind of nonlinear networks, and provide an applicative example based on the nonlinear, widely-used, Lotka-Volterra model. DOI 10.0000/issn-2220-8879-networkbiology-2015-v5-0003 http://www.iaees.org/publications/journals/nb/articles/2015-5(1)/evolutionary-network-control-holds-for-nonlinear-networks.pdf