Gene expression and metadata based identification of key genes for lung cancer, COPD, and IPF using machine learning and statistical models - PubMed
5 hours ago
- #bioinformatics
- #machine learning
- #lung cancer
- Identifies key genes (ETS1, MSH2, RORA, PMAIP1) for lung cancer (LC), COPD, and IPF using machine learning and bioinformatics.
- Uses differential gene expression analysis (DEGs) and protein-protein interaction (PPI) networks to pinpoint hub genes.
- Conducts KEGG and cancer pathway studies to understand disease mechanisms.
- Integrates network-based methodologies, including transcription factors and gene-miRNA relationships, to refine gene candidates.
- Proposes potential drug compounds targeting identified genes for therapeutic development.
- Provides a foundation for future research and treatment strategies for LC, COPD, and IPF.