  Analysis of network dynamics became a focal point to understand and predict
changes of complex systems. Here we introduce Turbine, a generic framework
enabling fast simulation of any algorithmically definable dynamics on very
large networks. Using a perturbation transmission model inspired by
communicating vessels, we define a novel centrality measure: perturbation
centrality. Hubs and inter-modular nodes proved to be highly efficient in
perturbation propagation. High perturbation centrality nodes of the Met-tRNA
synthetase protein structure network were identified as amino acids involved in
intra-protein communication by earlier studies. Changes in perturbation
centralities of yeast interactome nodes upon various stresses well
recapitulated the functional changes of stressed yeast cells. The novelty and
usefulness of perturbation centrality was validated in several other model,
biological and social networks. The Turbine software and the perturbation
centrality measure may provide a large variety of novel options to assess
signaling, drug action, environmental and social interventions. The Turbine
algorithm is available at: http://www.turbine.linkgroup.hu
