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Large-scale molecular interaction networks are dynamic in nature and changes in these networks, rather than changes in individual genes/proteins, are often drivers of complex diseases such as cancer. In this talk, I use data from stage III melanoma patients provided by Prof. Mann lab that comprise of clinical, mRNA and miRNA data to discuss how network information can be utilise in the analysis of gene expression analysis to aid in biological interpretation. I will also present an R software package, Variability Analysis in Networks (VAN), that enables an integrative analysis of protein-protein or microRNA-gene networks and expression data to identify hubs (i.e. highly connected proteins/microRNAs in a network) that are dysregulated, in terms of expression correlation with their interaction partners.
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