Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction
This study identifies ribosome biogenesis as one of the pivotal molecular mechanisms to PE pathogenesis, leveraging SHAP-interpretable machine learning to pinpoint six biomarkers. Future research is requisite for the validation of CRISPR and the integration of multi-omics to translate the findings into clinical diagnosis and targeted therapy.
Authors
- Kejun Ye
- Lin Lin (ORCID: https://orcid.org/0000-0002-2832-7537)
- Jingjing Chen (ORCID: https://orcid.org/0000-0001-6612-0337)
- Mengjia Peng
- Ying Hua
- Dan Zhang (ORCID: https://orcid.org/0009-0005-4438-0206)
- C. G. Zhu
Institutions
- Wenzhou Medical University (CN)
- Ruian People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-06-09
- DOI
- https://doi.org/10.3389/fimmu.2025.1595222
- Citations
- 1
- Primary Topic
- Pregnancy and preeclampsia studies
- Type
- article
- Field-Weighted Citation Impact
- 2.06
Funders
- Wenzhou Municipal People's Government