Employing a synergistic bioinformatics and machine learning framework to elucidate biomarkers associating asthma with pyrimidine metabolism genes
This investigation identifies eleven PyMGs at the core of asthma's pathogenesis, establishing them as potential biomarkers for this disease. Our findings enhance the understanding of asthma's molecular mechanisms and open new avenues for improving diagnostics, monitoring, and progression evaluation. By providing new insights into non-cancerous pathologies, our work introduces a novel perspective and sets the stage for further studies in this field.
Authors
- Dihui Zhang (ORCID: https://orcid.org/0009-0006-3187-2436)
- Guanghui Li (ORCID: https://orcid.org/0000-0003-2290-1515)
- Man Zheng
- Jia Chen (ORCID: https://orcid.org/0000-0002-9256-7121)
- Xiaowei Pu
Institutions
- Guangzhou University of Chinese Medicine (CN)
- Wenzhou Medical University (CN)
- Shanghai University of Traditional Chinese Medicine (CN)
- Shandong Provincial Hospital (CN)
- Boxing People's Hospital (CN)
- Shuguang Hospital (CN)
- Dongyang People's Hospital (CN)
Publication Details
- Journal
- Respiratory Research
- Published
- 2024-08-31
- DOI
- https://doi.org/10.1186/s12931-024-02954-4
- Citations
- 3
- Primary Topic
- RNA modifications and cancer
- Type
- article
- Field-Weighted Citation Impact
- 0.70
Funders
- Shanghai University of Traditional Chinese Medicine