Analysis of network dynamics became increasingly important to understand the mechanisms and consequences of changes in biological systemsfrom macromolecules to cells URLanisms. Currently available network dynamics tools are mostly tailored for specific tasks such as calculation of molecular or neural dynamics. Our Turbinesoftware offers a generic framework enabling the simulation of any algorithmically definable dynamics of any network. Turbine is also optimized for handling very large networks in the range of millions of nodes and edges . Using a perturbation transmission model inspired by communicating vessels, here we introduce a novel centrality measure termed as perturbation centrality. Perturbation centrality is the reciprocal of the time needed to dissipate a starting perturbation in the network. 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 substrate binding and allosteric communication by earlier studies. Changes in perturbation centralities of yeast protein-protein interaction network nodes upon various stresses well recapitulated the functional changes of stressed yeast cells. The  Turbine software and the perturbation centrality measure  provide a large variety of novel options for future studies on network robustness, signalingmechanisms and drug design.
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: URL
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increasingly important to understand the mechanisms and consequences of changes in biological systemsfrom macromolecules to cells URLanisms. Currently available network dynamics tools are mostly tailored for specific tasks such as calculation of molecular or neural dynamics. Our Turbinesoftware offers
a focal point to understand and predict changes of complex systems. Here we introduce Turbine,
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novelty and usefulness of perturbation centrality was validated in several other model, biological and social networks. The
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for future studies on network robustness, signalingmechanisms and drug design.
to assess signaling, drug action, environmental and social interventions. The Turbine algorithm is available at: URL