期刊
CURRENT OPINION IN MICROBIOLOGY
卷 31, 期 -, 页码 124-131出版社
CURRENT BIOLOGY LTD
DOI: 10.1016/j.mib.2016.03.008
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资金
- Exxon Mobil
- National Institute of Biomedical Imaging And Bioengineering of the National Institutes of Health [T32EB009412]
- U.S. Dept. of Energy [DE-AC02-06CH11357]
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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