Machine learning interprets genome sequences to map possible microbial symbionts.

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DOI: 10.1038/s41587-026-03212-2
Published: 2026 Sep 2
Container: Nature biotechnology
Publisher: Not recorded
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Cite this work

BibTeX

@article{allodium:10.1038/s41587-026-03212-2,
  title = {Machine learning interprets genome sequences to map possible microbial symbionts.},
  year = {2026},
  journal = {Nature biotechnology},
  doi = {10.1038/s41587-026-03212-2},
  url = {https://doi.org/10.1038/s41587-026-03212-2}
}

RIS

TY  - JOUR
TI  - Machine learning interprets genome sequences to map possible microbial symbionts.
PY  - 2026
JO  - Nature biotechnology
DO  - 10.1038/s41587-026-03212-2
UR  - https://doi.org/10.1038/s41587-026-03212-2
ER  -

APA

Machine learning interprets genome sequences to map possible microbial symbionts.. (2026). Nature biotechnology. https://doi.org/10.1038/s41587-026-03212-2

Source records

pubmed · retrieved 2026-09-25T05:52:20.108Z