Students learn about complex networks and how to represent them using graphs. They also learn that graph theory is a useful
mathematical tool for studying complex networks in diverse applications of science and engineering, such as neural networks
in the brain, biochemical reaction networks in cells, communication networks, such as the internet, and social networks. Topics
covered include set theory, defining a graph, as well as defining the degree of a node and the degree distribution of a graph.
other Citation Details
Cinergi keyword enhanced.File generated at Wed Aug 15 22:24:34 UTC 2018
Resource language:
Constraints on resource usage:
Legal Constraints
Access Constraints
otherRestrictions
use constraint:
otherRestrictions
Resource extent
Extent description
Applicable Everywhere
Geographic Extent
Geographic Bounding Box
westBoundLongitude
180
eastBoundLongitude
180
northBoundLatitude
90
southBoundLatitude
90
point of contact
-
pointOfContact
individual Name TeachEngineering.org TeachEngineering.org Complex Systems Science Laboratory, Garrett Jenkinson and John Goutsias, The Johns
Hopkins University, Baltimore, MD Debbie Jenkinson and Susan Frennesson, The Pine School, Stuart, FL Support
organisation Name
TeachEngineering.org TeachEngineering.org Complex Systems Science Laboratory, Garrett Jenkinson and John Goutsias, The Johns
Hopkins University, Baltimore, MD Debbie Jenkinson and Susan Frennesson, The Pine School, Stuart, FL
organisation Name
TeachEngineering.org TeachEngineering.org Complex Systems Science Laboratory, Garrett Jenkinson and John Goutsias, The Johns
Hopkins University, Baltimore, MD Debbie Jenkinson and Susan Frennesson, The Pine School, Stuart, FL
Metadata scope code
dataset
Metadata language
Metadata character set encoding:
utf8
Metadata standard for this record:
WMO Core Metadata Profile of ISO 19115 (WMO Core), 2003/Cor.1:2006 (ISO 19115), 2007 (ISO/TS 19139)
standard version:
1.3
Metadata record identifier:
11510/20121121233346534M
Metadata record format is ISO19139-2 XML (MI_Metadata)