Author

M. Gençtürk

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Open access Nov 2025

Bridging Local and Federated Data Normalization in Federated Learning: A Privacy-Preserving Approach

Data normalization is a crucial preprocessing step for enhancing model performance and training stability. In federated learning (FL), where data remains distributed across multiple parties during collaborative model training, normalization presents unique challenges due to the decentralized and often heterogeneous nat...

Melih Coşğun, M. Gençtürk, Sinem Sav · IEEE Transactions on Big Dat... · 1 citation

Open access Aug 2026

REFCON: Reference-free and robust copy number inference in single-cell tumor transcriptomes

REFCON is introduced, a deep-learning model that enables reference-free copy number profiling from scRNA-seq data collected without matched normals, and profiles pure tumors, generalizes to unseen tissues and platforms, and stays robust to cohort composition.

M. Gençtürk, A. E. Cicek · bioRxiv · 0 citations