Discovering bipartite substructure in directed networks

Alan Taylor, J. Keith Vass, Desmond J. Higham

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
65 Downloads (Pure)


Bipartivity is an important network concept that can be applied to nodes, edges and communities. Here we focus on directed networks and look for subnetworks made up of two distinct groups of nodes, connected by “one-way” links. We show that a spectral approach can be used to find hidden substructure of this form. Theoretical support is given for the idealised case where there is limited overlap between subnetworks. Numerical experiments show that the approach is robust to spurious and missing edges. A key application of this work is in the analysis of high-throughput gene expression data, and we give an example where a biologically meaningful directed bipartite subnetwork is found from a cancer microarray dataset.
Original languageEnglish
Pages (from-to)72-86
Number of pages15
JournalLMS Journal of Computation and Mathematics
Publication statusPublished - 30 Nov 2011


  • bipartite substructure
  • directed networks
  • subnetworks
  • discovering


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