Revealing networks from dynamics: an introduction
Adaptation and Self-Organizing Systems
2014-08-14 v1 Biological Physics
Physics and Society
Molecular Networks
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.
Cite
@article{arxiv.1408.2963,
title = {Revealing networks from dynamics: an introduction},
author = {Marc Timme and Jose Casadiego},
journal= {arXiv preprint arXiv:1408.2963},
year = {2014}
}
Comments
Topical review, 48 pages, 7 figures