Author

M. Temiz

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Open access Sep 2026

Knowledge-Driven Feature Selection with the Grouping–Scoring–Modeling Framework for Biomarker Discovery in High-Dimensional Transcriptomic Data

Biomarker discovery from high-dimensional transcriptomic data is frequently hindered by the “curse of dimensionality” and model selection bias. To address this, we propose the Grouping–Scoring–Modeling (G-S-M) framework, a knowledge-driven pipeline that anchors feature selection in established disease–gene associations...

Malik Yousef, Jens Allmer, Yasin Inal et al. · Applied Sciences · 0 citations