Fig. 1
The methodology process for the investigation is presented in a workflow. Gene expression data from the GSE10334 dataset was obtained from the GEO repository and preprocessed using various machine learning techniques. Ensemble machine learning models, including boosting and bagging approaches, were employed to classify the data and extract feature importance through cross-validation. Identified features were subjected to bioinformatics analyses such as PPI network construction, GO and pathway analysis, hub gene identification, and CNA analysis. This comprehensive pipeline offers insights into gene expression, biological pathways, and functional mechanisms.
