MegaD: Deep Learning for Rapid and Accurate Disease Status Prediction of Metagenomic Samples.

ABSTRACT: The diversity within different microbiome communities that drive biogeochemical processes influences many different phenotypes. Analyses of these communities and their diversity by countless microbiome projects have revealed an important role of metagenomics in understanding the complex relation between microbes and their environments. This relationship can be understood in the context of microbiome composition of specific known environments. These compositions can then be used as a template for predicting the status of similar environments. Machine learning has been applied as a key component to this predictive task. Several analysis tools have already been published utilizing machine learning methods for metagenomic analysis. Despite the previously proposed machine learning models, the p

SUBMITTER: Mreyoud Y 

PROVIDER: S-EPMC9143510 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature