Predicting environmental stressor levels with machine learning: a comparison between amplicon sequencing, metagenomics, and total RNA sequencing based on taxonomically assigned data

Predicting environmental stressor levels with machine learning: a comparison between amplicon sequencing, metagenomics, and total RNA sequencing based on taxonomically assigned data

IntroductionMicrobes are increasingly (re)considered for environmental assessments because they are powerful indicators for the health of ecosystems. The complexity of microbial communities necessitates powerful novel tools to derive conclusions for environmental decision-makers, and machine learnin...

Full description

Bibliographic Details
Main Authors: Christopher A. Hempel, Dominik Buchner, Leoni Mack, Marie V. Brasseur, Dan Tulpan, Florian Leese, Dirk Steinke
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-11-01
Series:Frontiers in Microbiology
Subjects:
metabarcoding
metatranscriptomics
freshwater
stressor prediction
bioinformatics
ExStream
Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2023.1217750/full

Internet

https://www.frontiersin.org/articles/10.3389/fmicb.2023.1217750/full

Similar Items