Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition.

ABSTRACT: Microbial communities are ubiquitous and often influence macroscopic properties of the ecosystems they inhabit. However, deciphering the functional relationship between specific microbes and ecosystem properties is an ongoing challenge owing to the complexity of the communities. This challenge can be addressed, in part, by integrating the advances in DNA sequencing technology with computational approaches like machine learning. Although machine learning techniques have been applied to microbiome data, use of these techniques remains rare, and user-friendly platforms to implement such techniques are not widely available. We developed a tool that implements neural network and random forest models to perform regression and feature selection tasks on microbiome data. In this study, we applied

SUBMITTER: Thompson J 

PROVIDER: S-EPMC6602172 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature