Host-associated microbial communities are unique to individuals, affect host health, and correlate with disease states. Although advanced technologies capture detailed snapshots of microbial communities, high within- and between-subject variation hampers discovery of microbial signatures in diagnostic or forensic settings. We suggest turning to machine learning and discuss key directions toward harnessing human-associated microbial signatures.
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