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Revealing networks from dynamics: an introduction

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Timme,  Marc
Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Casadiego Bastidas,  José Luis
Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Citation

Timme, M., & Casadiego Bastidas, J. L. (2014). Revealing networks from dynamics: an introduction. Journal of Physics A: Mathematical and Theoretical, 47: 343001. doi:10.1088/1751-8113/47/34/343001.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0029-0F15-4
Abstract
What can we learn from the collective dynamics of a complex network about its interaction topology? Taking the perspective from nonlinear dynamics, we briefly review recent progress on how to infer structural connectivity (direct interactions) from accessing the dynamics of the units. Potential applications range from interaction networks in physics, to chemical and metabolic reactions, protein and gene regulatory networks as well as neural circuits in biology and electric power grids or wireless sensor networks in engineering. Moreover, we briefly mention some standard ways of inferring effective or functional connectivity.