1140-Evaluating Feature Reduction Methods for Drug model

Paper Talk · Jun 16, 2026 · 24m

This study evaluates various feature reduction (FR) techniques to enhance drug response prediction (DRP) using machine learning on high-dimensional molecular data. Researchers compared nine knowledge-based and data-driven methods across thousands of tests involving cancer cell lines and human tumor samples. While techniques like sparse principal components and Landmark genes performed well on cell lines, transcription factor (TF) activities proved most effective for predicting responses in complex clinical tumors. Across all tested scenarios, ridge regression emerged as the most robust…