In the continuing quest to relate microbial communities in bioreactors to function and environmental and operational conditions, engineers and biotechnologists have adopted the latest molecular and 'omic methods. Despite the large amounts of data generated, gaining mechanistic insights and using the data for predictive and practical purposes is still a huge challenge. We present a methodological framework that can guide experimental design, and discuss specific issues that can affect how researchers generate and use data to elucidate the relationships. We also identify, in general terms, bioreactor research opportunities that appear promising.
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