Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6131535 | Current Opinion in Microbiology | 2016 | 8 Pages |
Abstract
Network inference is being applied to studies of microbial ecology to visualize and characterize microbial communities. Network representations can allow examination of the underlying organizational structure of a microbial community, and identification of key players or environmental conditions that influence community assembly and stability. Microbial co-association networks provide information on the dynamics of community structure as a function of time or other external variables. Community metabolic networks can provide a mechanistic link between species through identification of metabolite exchanges and species specific resource requirements. When used together, co-association networks and metabolic networks can provide a more in-depth view of the hidden rules that govern the stability and dynamics of microbial communities.
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Authors
Cesar Cardona, Pamela Weisenhorn, Chris Henry, Jack A Gilbert,