Identification of crucial genes for polycystic ovary syndrome and atherosclerosis through comprehensive bioinformatics analysis and machine learning
Common therapeutic targets of PCOS and atherosclerosis were preliminarily identified through bioinformatics analysis and machine learning techniques. These findings provide new treatment ideas for reducing the risk that PCOS will develop into atherosclerosis.
Authors
- Chichiu Wang
- Fan Ji
- Yanli Zhang (ORCID: https://orcid.org/0000-0001-9661-3730)
- Lirong Wang (ORCID: https://orcid.org/0000-0002-9092-6282)
- Xiaoke Wu (ORCID: https://orcid.org/0000-0002-8339-9242)
- Chengdong Liu (ORCID: https://orcid.org/0000-0002-3419-4873)
- Hui Chang (ORCID: https://orcid.org/0000-0001-6891-1239)
- Zhenjing Si
Institutions
- Jiangsu University (CN)
- Chinese University of Hong Kong (HK)
- Heilongjiang University of Chinese Medicine (CN)
- First Affiliated Hospital of Heilongjiang University of Chinese Medicine (CN)
- Affiliated Hospital of Jiangsu University (CN)
- Heilongjiang Provincial Hospital (CN)
Publication Details
- Journal
- International Journal of Gynecology & Obstetrics
- Published
- 2025-02-21
- DOI
- https://doi.org/10.1002/ijgo.70014
- Citations
- 1
- Primary Topic
- Atherosclerosis and Cardiovascular Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.80
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Heilongjiang Province