Microbial communities are thought to contain keystone species, which can disproportionately affect the stability of the communities, even if only present in low abundances. Identifying these keystone species can be challenging, especially in the human gut, since it is not feasible to isolate them through systematic elimination. Researchers have designed a new data-driven keystone species identification (DKI) framework that uses machine learning to resolve this difficulty.
