@article{newmanStructureFunctionComplex2003,
	title = {The {Structure} and {Function} of {Complex} {Networks}},
	volume = {45},
	issn = {1958-5969},
	url = {http://arxiv.org/abs/cond-mat/0303516},
	doi = {10.1137/S003614450342480},
	abstract = {Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.},
	number = {2},
	journal = {SIAM REVIEW},
	author = {Newman, Mark E. J.},
	year = {2003},
	keywords = {05c75, 05c90, 94c15, Animals, Brain, Brain Mapping, Brain Mapping: methods, Brain: anatomy \& histology, Brain: physiology, Disordered Systems and Neural Networks, FNSA, Humans, Nerve Net, Nerve Net: anatomy \& histology, Nerve Net: physiology, Neural Pathways, Neural Pathways: anatomy \& histology, Neural Pathways: physiology, Neuroimaging, Neuroimaging: methods, Psychomotor Performance, Psychomotor Performance: physiology, Rest, Rest: physiology, Statistical Mechanics, ams subject classifications, complex systems, computer networks, graph theory, graphs, networks, percolation theory, pii, random, s0036144503424804, social networks},
	pages = {167--256},
}

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