Work

TCGA-THCA miRNA Machine-Learning Analysis

Year: 2026

Type: software

Abstract: Computational workflow for TCGA-THCA miRNA expression analysis, including data preprocessing, feature selection, class-imbalance handling, patient-grouped nested cross-validation, machine-learning model evaluation, TOPSIS ranking, feature-stability analysis, and derivation of a 30-miRNA candidate biomarker panel for thyroid cancer.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.23026953

Authors: Vural, Duru, Köroğlu, Seyit Metin, İzzetoğlu, Savaş

Language: English

Topic: MicroRNA in disease regulation

Subfield: Cancer Research

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7214735754

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