…Our new R package!
Methods developed in social network science have been successfully applied in the biomedical domain over for the past two decades. Examples include splitting biological networks into communities, to discover highly enriched complexes with specific diseases and functions. We developed the Bioconductor package BioNAR to provide biomedical researchers with a network analysis ‘toolkit’, containing in one place many of the basic network analysis functionality required to analysis their data. When applied to PPI networks the package can predict a proteins impact within multiple complexes, and estimate the co-occurrence of a lab’s meta-data, i.e. disease and function, across the network pointing towards shared/common mechanisms. Future releases aim to include functionality to analysis very large networks, by integrating with HPC clusters and access to graph-oriented databases, and inclusion of probabilistic network analysis algorithms based on Bayesian inference, to further utilise both vertex and edge meta-data.
Additional information can be found here.