Gene expression analysis workflow with Autoencoders, Random forest algorithm, and Z-score, and DAE-Lin with Random forest algorithm, and Z-score
Abstract
A comprehensive workflow for gene expression data analysis using various autoencoder architectures and proposed DAE-Lin for dimensionality reduction, Random Forest feature importance analysis, and cross-dataset Z-score analysis.
Publication details
- Journal / source
- Figshare
- Publication date
- 2 January 2026