Machine learning-based linking of bacterial genomes to optimal growth pH: a foundation for rational microbial engineering.
- DOI
- 10.1186/s40104-026-01434-7
- Published
- 2026 Jun 11
- Container
- Journal of animal science and biotechnology
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1186/s40104-026-01434-7,
title = {Machine learning-based linking of bacterial genomes to optimal growth pH: a foundation for rational microbial engineering.},
author = {Chen H and Yang X and Anas MA and Feng S and Lin Y and Xu G and Ni K and Yang F and Wang X},
year = {2026},
journal = {Journal of animal science and biotechnology},
doi = {10.1186/s40104-026-01434-7},
url = {https://doi.org/10.1186/s40104-026-01434-7}
}RIS
TY - JOUR TI - Machine learning-based linking of bacterial genomes to optimal growth pH: a foundation for rational microbial engineering. AU - Chen H AU - Yang X AU - Anas MA AU - Feng S AU - Lin Y AU - Xu G AU - Ni K AU - Yang F AU - Wang X PY - 2026 JO - Journal of animal science and biotechnology DO - 10.1186/s40104-026-01434-7 UR - https://doi.org/10.1186/s40104-026-01434-7 ER -
APA
H, C., X, Y., MA, A., S, F., Y, L., G, X., K, N., F, Y., & X, W. (2026). Machine learning-based linking of bacterial genomes to optimal growth pH: a foundation for rational microbial engineering.. Journal of animal science and biotechnology. https://doi.org/10.1186/s40104-026-01434-7
Source records
- pubmed · retrieved 2026-09-25T18:52:15.228Z