dorsal/arxiv
View SchemaUsing graph concepts to understand the organization of complex systems
| Authors | Claire Christensen, Reka Albert |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0609036 |
| URL | https://arxiv.org/abs/q-bio/0609036 |
| DOI | 10.1142/S021812740701835X |
Abstract
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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"abstract": "Complex networks are universal, arising in fields as disparate as sociology,\nphysics, and biology. In the past decade, extensive research into the\nproperties and behaviors of complex systems has uncovered surprising\ncommonalities among the topologies of different systems. Attempts to explain\nthese similarities have led to the ongoing development and refinement of\nnetwork models and graph-theoretical analysis techniques with which to\ncharacterize and understand complexity. In this tutorial, we demonstrate\nthrough illustrative examples, how network measures and models have contributed\nto the elucidation of the organization of complex systems.",
"arxiv_id": "q-bio/0609036",
"authors": [
"Claire Christensen",
"Reka Albert"
],
"categories": [
"q-bio.OT",
"cond-mat.dis-nn",
"q-bio.MN"
],
"doi": "10.1142/S021812740701835X",
"title": "Using graph concepts to understand the organization of complex systems",
"url": "https://arxiv.org/abs/q-bio/0609036"
},
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