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Taking advantage of the fast time scale and ease of setting up a controlled experiment, we study complex ecological dynamics that arise from microbial community interactions.
To investigate the differences in the interactions of microbial communities in two regions in Taihu Lake with different nutrient loadings [Meiliang Bay (MLB) and Xukou Bay (XKB ], water samples were collected and both intra- and inter-kingdom microbial community interactions were examined with network analysis.
Generalized Lotka Volterra (gLV) equations are used to study these complex types of dynamic microbial community interactions [77].
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Despite this fact, few metagenomic studies use pathway-centric approaches to predict microbial community interaction networks based on known biochemical rules.
The use of these approaches, in combination with detailed reactor performance data, can provide a new opportunity to develop a fundamental understanding of how microbial community dynamics, interactions, and functionality influence the efficiency of anaerobic wastewater treatment processes.
The use of these approaches in combination with complementary imaging techniques, chemical isotope analyses and detailed reactor performance measurements provides a new opportunity to develop a fundamental understanding of how microbial community dynamics, interactions and functionality influence digester efficiency and stability.
To optimize the operational parameters and process design of BES a better comprehension of the microbial community dynamics and interactions at the anode is required.
The structure and relative abundance of the microbial community, especially the interactions between different microorganisms, have great influence on promoting IMEOR.
It is possible that LCOs, although produced by rhizobia, have a direct influence on the rhizospheric microbial community by influencing interactions among microorganisms and promoting plant growth, including growth of non-host plants.
5 - [ 20] The availability of these metagenomes provides an opportunity to examine the microbial community composition and interactions present in these mixed microbial systems, bypassing the rigorous requirement of isolation of community members and complete genome sequencing.
Analyzing microbial community structure revealed potential interactions between Ignicoccus and an archaeal parasite Nanoarchaea.
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