Machine Learning Predicts the Presence of 2,4,6-Trinitrotoluene in Sediments of a Baltic Sea Munitions Dumpsite Using Microbial Community Compositions

Machine Learning Predicts the Presence of 2,4,6-Trinitrotoluene in Sediments of a Baltic Sea Munitions Dumpsite Using Microbial Community Compositions

Bacteria are ubiquitous and live in complex microbial communities. Due to differences in physiological properties and niche preferences among community members, microbial communities respond in specific ways to environmental drivers, potentially resulting in distinct microbial fingerprints for a giv...

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Bibliographic Details
Main Authors: René Janßen, Aaron J. Beck, Johannes Werner, Olaf Dellwig, Johannes Alneberg, Bernd Kreikemeyer, Edmund Maser, Claus Böttcher, Eric P. Achterberg, Anders F. Andersson, Matthias Labrenz
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Microbiology
Subjects:
munition compounds
Kolberger Heide
mercury
random forest
16S rRNA gene amplicon sequencing
monitoring
Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2021.626048/full

Internet

https://www.frontiersin.org/articles/10.3389/fmicb.2021.626048/full

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