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Journals / İstanbul Ticaret Üniversitesi Teknoloji ve Uygulamalı Bilimler Dergisi / 2025 / Cilt: 8 Sayı: 1

Advancing Cancer Classification: Machine Learning Applications on RNA-Seq Gene Expression Data

Kanser Sınıflandırmasını Geliştirme: RNA-Seq Gen EkspresyonuVerileri Üzerinde Makine Öğrenimi Uygulamaları

Büşra Çetinkaya(İSTANBUL TİCARET ÜNİVERSİTESİ)0009-0006-6971-4257
Mustafa Cem Kasapbaşı(İstanbul Ticaret Üniversitesi Mühendislik Fakültesi)0000-0001-6444-6659
Pages
133–141
Publication Date
2025-08-26
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

These data are used to evaluate the effectiveness of machine learning algorithms in cancer diagnosis and classification.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study addresses the analysis of RNA-seq gene expression data using machine learning techniques to improve cancer classification.
📊
Key Findings & Data:The dataset obtained from the UCI Machine Learning Repository contains gene expression levels for different types of cancer.
💡
Conclusion & Impact:These data are used to evaluate the effectiveness of machine learning algorithms in cancer diagnosis and classification.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Kanser · RNA Sekanslanma · Veri Analizi

Abstract

This study addresses the analysis of RNA-seq gene expression data using machine learning techniques to improve cancer classification. The dataset obtained from the UCI Machine Learning Repository contains gene expression levels for different types of cancer. These data are used to evaluate the effectiveness of machine learning algorithms in cancer diagnosis and classification.

Özet

Bu çalışma, kanser sınıflandırmasını geliştirmek amacıyla RNA-seq gen ekspresyonu verilerinin makine öğrenimi teknikleri ile analizini ele almaktadır. UCI Machine Learning Repository'den elde edilen veri seti, farklı kanser türlerine ait gen ifade seviyelerini içermektedir. Bu veriler, makine öğrenimi algoritmalarının kanser teşhisi ve sınıflandırmasındaki etkinliğini değerlendirmek için kullanılmaktadır.

🔖

Cite This Article

Çetinkaya, B., Kasapbaşı, M. C. (2025). Advancing Cancer Classification: Machine Learning Applications on RNA-Seq Gene Expression Data. İstanbul Ticaret Üniversitesi Teknoloji ve Uygulamalı Bilimler Dergisi, Cilt: 8 Sayı: 1, 133–141. https://doi.org/10.56809/icujtas.1609317

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