Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province
- DOI
- 10.3389/fmicb.2025.1586195
- Published
- 2025-07-11
- Container
- Frontiers in Microbiology
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fmicb.2025.1586195,
title = {Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province},
author = {Li Luo and Bangwei Chen and Shengyin Zeng and Yaxin Li and Xiaolin Chen and Jianguo Zhang and Xiangjie Guo and Shujin Li and Lei Ruan and Shida Zhu and Cairong Gao and Cuntai Zhang and Tao Li},
year = {2025},
journal = {Frontiers in Microbiology},
doi = {10.3389/fmicb.2025.1586195},
url = {https://doi.org/10.3389/fmicb.2025.1586195}
}RIS
TY - JOUR TI - Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province AU - Li Luo AU - Bangwei Chen AU - Shengyin Zeng AU - Yaxin Li AU - Xiaolin Chen AU - Jianguo Zhang AU - Xiangjie Guo AU - Shujin Li AU - Lei Ruan AU - Shida Zhu AU - Cairong Gao AU - Cuntai Zhang AU - Tao Li PY - 2025 JO - Frontiers in Microbiology DO - 10.3389/fmicb.2025.1586195 UR - https://doi.org/10.3389/fmicb.2025.1586195 ER -
APA
Luo, L., Chen, B., Zeng, S., Li, Y., Chen, X., Zhang, J., Guo, X., Li, S., Ruan, L., Zhu, S., Gao, C., Zhang, C., & Li, T. (2025). Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2025.1586195
Source records
- crossref · retrieved 2026-09-25T19:06:58.344Z