Assortative mixing in directed biological networks

Mahendra Piraveenan*, Mikhail Prokopenko, Albert Zomaya

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

81 Citations (Scopus)

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.

Original languageEnglish
Article number5557854
Pages (from-to)66-78
Number of pages13
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume9
Issue number1
DOIs
Publication statusPublished - 2012
Externally publishedYes

Keywords

  • assortativity
  • biological networks
  • graph theory
  • Networks
  • systems biology

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