Author

Burcu Bakir-Gungor

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Open access Sep 2026

A Disease-Guided Representative Gene Selection Framework for High-Dimensional Gene Expression Analysis

Gene expression datasets provide valuable information for disease classification and biomarker discovery; however, their high dimensionality and limited sample size may limit classification performance and reduce biological interpretability. This study proposes GeDiRep, a prior knowledge-guided framework for identifyin...

Cihan Kuzudisli, B. Qaqish, Burcu Bakir-Gungor et al. · Mathematics · 0 citations

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

Conference Jul 2026

Explainable Machine Learning for Cross-Sectional Stock Return Prediction and Mean–Variance Portfolio Optimization

Portfolio construction aims to balance expected return and risk through effective asset allocation. This study proposes a portfolio formation framework that integrates machine learning-based return prediction with Markowitz mean–variance portfolio optimization. Random Forest, XGBoost, Multilayer Perceptron, and Support...

Mustafa Etcil, Hüseyin Akkaş, Burak Kolukısa et al. · Signal Processing and Commun... · 0 citations