MMETHANE: interpretable AI for predicting host status from microbial composition and metabolomics data.

Dawkins JJ, Gerber GK

DOI: 10.1101/2024.12.13.628441
Published: 2024 Dec 14
Container: bioRxiv : the preprint server for biology
Publisher: Not recorded
Open access: yes

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BibTeX

@article{allodium:10.1101/2024.12.13.628441,
  title = {MMETHANE: interpretable AI for predicting host status from microbial composition and metabolomics data.},
  author = {Dawkins JJ and Gerber GK},
  year = {2024},
  journal = {bioRxiv : the preprint server for biology},
  doi = {10.1101/2024.12.13.628441},
  url = {https://doi.org/10.1101/2024.12.13.628441}
}

RIS

TY  - JOUR
TI  - MMETHANE: interpretable AI for predicting host status from microbial composition and metabolomics data.
AU  - Dawkins JJ
AU  - Gerber GK
PY  - 2024
JO  - bioRxiv : the preprint server for biology
DO  - 10.1101/2024.12.13.628441
UR  - https://doi.org/10.1101/2024.12.13.628441
ER  -

APA

JJ, D., & GK, G. (2024). MMETHANE: interpretable AI for predicting host status from microbial composition and metabolomics data.. bioRxiv : the preprint server for biology. https://doi.org/10.1101/2024.12.13.628441

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pubmed · retrieved 2026-09-27T15:25:18.206Z