Identification and validation of circadian rhythm-related diagnostic biomarkers for endometriosis through integrating machine learning and single-cell analysis
- DOI
- 10.1016/j.ejogrb.2026.115521
- Published
- 2027-01
- Container
- European Journal of Obstetrics & Gynecology and Reproductive Biology
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.ejogrb.2026.115521,
title = {Identification and validation of circadian rhythm-related diagnostic biomarkers for endometriosis through integrating machine learning and single-cell analysis},
author = {Donglin Chen and Lixia Xu and Lin Cheng and Aifang Su},
year = {2027},
journal = {European Journal of Obstetrics \& Gynecology and Reproductive Biology},
doi = {10.1016/j.ejogrb.2026.115521},
url = {https://doi.org/10.1016/j.ejogrb.2026.115521}
}RIS
TY - JOUR TI - Identification and validation of circadian rhythm-related diagnostic biomarkers for endometriosis through integrating machine learning and single-cell analysis AU - Donglin Chen AU - Lixia Xu AU - Lin Cheng AU - Aifang Su PY - 2027 JO - European Journal of Obstetrics & Gynecology and Reproductive Biology DO - 10.1016/j.ejogrb.2026.115521 UR - https://doi.org/10.1016/j.ejogrb.2026.115521 ER -
APA
Chen, D., Xu, L., Cheng, L., & Su, A. (2027). Identification and validation of circadian rhythm-related diagnostic biomarkers for endometriosis through integrating machine learning and single-cell analysis. European Journal of Obstetrics & Gynecology and Reproductive Biology. https://doi.org/10.1016/j.ejogrb.2026.115521
Source records
- crossref · retrieved 2026-11-09T18:26:29.138Z