Predicting microbiome compositions from species assemblages through deep learning.

ABSTRACT: Microbes can form complex communities that perform critical functions in maintaining the integrity of their environment or their hosts' well-being. Rationally managing these microbial communities requires improving our ability to predict how different species assemblages affect the final species composition of the community. However, making such a prediction remains challenging because of our limited knowledge of the diverse physical, biochemical, and ecological processes governing microbial dynamics. To overcome this challenge, we present a deep learning framework that automatically learns the map between species assemblages and community compositions from training data only, without knowing any of the above processes. First, we systematically validate our framework using synthetic data g

SUBMITTER: Michel-Mata S 

PROVIDER: S-EPMC9221840 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature