Machine learning and in vivo evidence identify CCNB2 as a candidate biomarker of 2-aminobenzothiazole-induced hepatotoxicity in Carassius auratus
- DOI
- 10.1016/j.aquatox.2026.108069
- Published
- 2027-01
- Container
- Aquatic Toxicology
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.aquatox.2026.108069,
title = {Machine learning and in vivo evidence identify CCNB2 as a candidate biomarker of 2-aminobenzothiazole-induced hepatotoxicity in Carassius auratus},
author = {Yunshan Zhang and Yanming Zhang and Tianmeng Shao and Weihua Chu},
year = {2027},
journal = {Aquatic Toxicology},
doi = {10.1016/j.aquatox.2026.108069},
url = {https://doi.org/10.1016/j.aquatox.2026.108069}
}RIS
TY - JOUR TI - Machine learning and in vivo evidence identify CCNB2 as a candidate biomarker of 2-aminobenzothiazole-induced hepatotoxicity in Carassius auratus AU - Yunshan Zhang AU - Yanming Zhang AU - Tianmeng Shao AU - Weihua Chu PY - 2027 JO - Aquatic Toxicology DO - 10.1016/j.aquatox.2026.108069 UR - https://doi.org/10.1016/j.aquatox.2026.108069 ER -
APA
Zhang, Y., Zhang, Y., Shao, T., & Chu, W. (2027). Machine learning and in vivo evidence identify CCNB2 as a candidate biomarker of 2-aminobenzothiazole-induced hepatotoxicity in Carassius auratus. Aquatic Toxicology. https://doi.org/10.1016/j.aquatox.2026.108069
Source records
- crossref · retrieved 2026-11-05T04:18:47.148Z