Mesoscale Analyses of Fungal Networks

We investigate the application of mesoscopic response functions (MRFs) to characterise a large set of networks of fungi and slime moulds grown under a wide variety of different experimental treatments, including inter-species competition and attack by fungivores. We construct "structural networks" by estimating cord conductances (which yield edge weights) from the experimental data, and we construct "functional networks" by calculating edge weights based on how much nutrient traffic is predicted to occur on each edge. Both types of networks have the same topology, and we compute MRFs for both families of networks to illustrate two different ways of constructing taxonomies to group the biological networks into related clusters. Although both network taxonomies generate intuitively sensible groupings of networks across species, treatments, and laboratories, we find that clustering using the functional-network measure appears to give more parsimonious groups. We argue that MRFs provide a useful quantitative measures of network behaviour that can help to summarise an expanding set of increasingly complex experimental biological networks and to present the information in an accessible form.