Supervised machine learning enables geospatial microbial provenance

HIGHLIGHTS

  • who: Chandrima Bhattacharya and colleagues from the New York, NY, USA Department of Biological Sciences, National University of Singapore, Singapore, Singapore have published the Article: Supervised Machine Learning Enables Geospatial Microbial Provenance, in the Journal: Genes 2022, 13, x FOR PEER REVIEW of /2022/
  • what: This investigation shows that, even from varied mixtures of microbial communities, the authors can uniquely predict the provenance of a given metagenomic sample by its microbial fingerprint. The authors explored whether microbial signatures from known sources and locations can be utilized for predicting the origin of an unknown sample.
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