Uncovering sodium overload-associated gene signatures in chronic obstructive pulmonary disease through integrated bioinformatics and machine learning.
- DOI
- 10.21037/jtd-2026-0843
- Published
- 2026 Aug 31
- Container
- Journal of thoracic disease
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.21037/jtd-2026-0843,
title = {Uncovering sodium overload-associated gene signatures in chronic obstructive pulmonary disease through integrated bioinformatics and machine learning.},
author = {Zou Z and Chen J and Mai Z and Wu N and Wang Y and Xu R and Jiang Z and Chen G and Xian L},
year = {2026},
journal = {Journal of thoracic disease},
doi = {10.21037/jtd-2026-0843},
url = {https://doi.org/10.21037/jtd-2026-0843}
}RIS
TY - JOUR TI - Uncovering sodium overload-associated gene signatures in chronic obstructive pulmonary disease through integrated bioinformatics and machine learning. AU - Zou Z AU - Chen J AU - Mai Z AU - Wu N AU - Wang Y AU - Xu R AU - Jiang Z AU - Chen G AU - Xian L PY - 2026 JO - Journal of thoracic disease DO - 10.21037/jtd-2026-0843 UR - https://doi.org/10.21037/jtd-2026-0843 ER -
APA
Z, Z., J, C., Z, M., N, W., Y, W., R, X., Z, J., G, C., & L, X. (2026). Uncovering sodium overload-associated gene signatures in chronic obstructive pulmonary disease through integrated bioinformatics and machine learning.. Journal of thoracic disease. https://doi.org/10.21037/jtd-2026-0843
Source records
- pubmed · retrieved 2026-09-26T15:52:09.874Z