Machine learning-driven exploration of therapeutic targets for atrial fibrillation-joint analysis of single-cell and bulk transcriptomes and experimental validation
This study provides new insights into the molecular mechanisms of AF and offers potential non-invasive biomarkers for AF diagnosis. The identified key genes and constructed model may facilitate the development of targeted therapies for AF.
Authors
- Jian-Cheng Zhang (ORCID: https://orcid.org/0000-0002-8848-5748)
- Hongyi Yang
- Zhaoqing Fan (ORCID: https://orcid.org/0000-0003-2968-1703)
- Yicheng Wang (ORCID: https://orcid.org/0009-0001-7835-7048)
Institutions
- Fujian Medical University (CN)
- Fujian Provincial Hospital (CN)
- Fuzhou University (CN)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2025-11-03
- DOI
- https://doi.org/10.3389/fcvm.2025.1652467
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Fujian Province