A biochemically-interpretable machine learning classifier for microbial GWAS
Current machine learning classifiers have been applied to whole-genome sequencing data to identify determinants of antimicrobial resistance, but they lack interpretability. Here the authors present a metabolic machine learning classifier that uses flux balance analysis to estimate the biochemical ef...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2020-05-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-020-16310-9 |