DocumentCode
1305296
Title
Assortative mixing in directed biological networks
Author
Piraveenan, M. ; Prokopenko, M. ; Zomaya, A.
Author_Institution
Sch. of Inf. Technol., Univ. of Sydney, Sydney, NSW, Australia
Volume
9
Issue
1
fYear
2012
Firstpage
66
Lastpage
78
Abstract
We analyze assortative mixing patterns of biological networks which are typically directed. We develop a theoretical background for analyzing mixing patterns in directed networks before applying them to specific biological networks. Two new quantities are introduced, namely the in-assortativity and the out-assortativity, which are shown to be useful in quantifying assortative mixing in directed networks. We also introduce the local (node level) assortativity quantities for in- and out-assortativity. Local assortativity profiles are the distributions of these local quantities over node degrees and can be used to analyze both canonical and real-world directed biological networks. Many biological networks, which have been previously classified as disassortative, are shown to be assortative with respect to these new measures. Finally, we demonstrate the use of local assortativity profiles in analyzing the functionalities of particular nodes and groups of nodes in real-world biological networks.
Keywords
network topology; assortative mixing patterns; biological networks; Bioinformatics; Biology; Book reviews; Computational biology; Equations; Probability distribution; Regulators; Networks; assortativity; biological networks.; graph theory; systems biology; Animals; Bacteria; Food Chain; Gene Regulatory Networks; Humans; Models, Biological; Nerve Net; Systems Biology;
fLanguage
English
Journal_Title
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher
ieee
ISSN
1545-5963
Type
jour
DOI
10.1109/TCBB.2010.80
Filename
5557854
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