BioNAR: an integrated biological network analysis package in bioconductor

Colin McLean, Anatoly Sorokin, Thomas Ian Simpson, James Douglas Armstrong, Oksana Sorokina*, Sofia Forslund (Editor)

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Biological function in protein complexes emerges from more than just the sum of their parts: molecules interact in a range of different sub-complexes and transfer signals/information around internal pathways. Modern proteomic techniques are excellent at producing a parts-list for such complexes, but more detailed analysis demands a network approach linking the molecules together and analysing the emergent architectural properties. Methods developed for the analysis of networks in social sciences have proven very useful for splitting biological networks into communities leading to the discovery of sub-complexes enriched with molecules associated with specific diseases or molecular functions that are not apparent from the constituent components alone.

Here, we present the Bioconductor package BioNAR, which supports step-by-step analysis of biological/biomedical networks with the aim of quantifying and ranking each of the network’s vertices based on network topology and clustering. Examples demonstrate that while BioNAR is not restricted to proteomic networks, it can predict a protein’s impact within multiple complexes, and enables estimation of the co-occurrence of metadata, i.e. diseases and functions across the network, identifying the clusters whose components are likely to share common function and mechanisms.

Availability and implementation:
The package is available from Bioconductor release 3.17:
Original languageEnglish
Article numbervbad137
Pages (from-to)1-10
Number of pages10
JournalBioinformatics Advances
Issue number1
Publication statusPublished - 17 Oct 2023


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