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13 Epilogue After the Panel Discussions
Pages 93-96

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From page 93...
... Many genomic tools currently exist that can reveal the organisms present within a microbiome, but there is a challenge in integrating different types of data to reveal underlying mechanisms. The lack of a comprehensive understanding of individual organisms genetic complement in communities limits understanding of how individuals collectively work together as functional microbiomes to chemically interact with each other and their environment.
From page 94...
... Such approaches could provide an outstanding framework for moving forward in microbiome chemistry research and asking important questions, such as how microbiomes may play critical roles in host function; microbiomes may be unseen instigators of interactions between higher organisms. Efforts may include understanding commonalities between microbiomes of different hosts, regions, and identifying whether patterns and similar interactions are occurring that can begin to formulate underlying principles of microbiome function.
From page 95...
... Computational models, such as community flux balance, are critical for understanding, predicting, and engineering complex microbiomes, but such efforts are nascent. New approaches that rapidly develop discoveries and new knowledge into models can bridge current knowledge gaps using computation biology.
From page 96...
... By simultaneously measuring fine-scale, dynamic chemical gradients -- in which microbial communities reside and interact -- with single cell measurements, we may be able to analyze the interactions between organisms at the scale that the interactions occur. The scale at which we currently probe the interactions between organisms is not at the scale interactions occur.

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