Using graph concepts to understand the organization of complex systems

Details Using graph concepts to understand the organization of complex systems Using graph concepts to understand the organization of complex systems

2006-09-24

arxiv.org/abs/q-bio/0609036v3

Biology

Quantitative Biology

Other Quantitative Biology

v(1) 38 pages, 7 figures, to appear in the International Journal of Bifurcation and Chaos v(2) Line spacing changed; now 23 pa

Scientific paper

Complex networks are universal, arising in fields as disparate as sociology, physics, and biology. In the past decade, extensive research into the properties and behaviors of complex systems has uncovered surprising commonalities among the topologies of different systems. Attempts to explain these similarities have led to the ongoing development and refinement of network models and graph-theoretical analysis techniques with which to characterize and understand complexity. In this tutorial, we demonstrate through illustrative examples, how network measures and models have contributed to the elucidation of the organization of complex systems.

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