ArticleMethods in molecular biology (Clifton, N.J.)2026
Estimating Effective Pairwise Interactions to Predict the Structures of Microbial Communities (EPICS).
Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The engineering of multispecies microbial communities is important to applications in healthcare, biotechnology, and environmental sustainability. Predicting the structures of such communities requires knowledge of the interactions between the species involved. When high-order interactions are present, bottom-up approaches, which rely on the assembly of all possible subcommunities, become prohibitive because the number of such subcommunities scales exponentially with the number of species. Here, we present an alternative, top-down approach, EPICS, which requires the assembly of subcommunities whose number scales linearly with the number of species, hugely reducing experimental effort. EPICS estimates effective pairwise interactions between species, which subsume high-order interactions, using data from monocultures and leave-one-out subcommunities and predicts community structures. The method is efficient and scalable to large communities.
Indexed as
Identifiers
42156654What OpenQuestion holds
Registered trials
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