Scopus
🔓 Açık Erişim YÖKSİS Eşleşti
Predicting human miRNA disease association with minimize matrix nuclear norm
Scientific Reports · Aralık 2024
YÖKSİS Kayıtları
Predicting human miRNA disease association with minimize matrix nuclear norm
Scientific Reports · 2024 SCI-Expanded
DOÇENT AHMET TOPRAK →
Makale Bilgileri
DergiScientific Reports
Yayın TarihiAralık 2024
Cilt / Sayfa14
Scopus ID2-s2.0-85213540490
Erişim🔓 Açık Erişim
Özet
microRNAs (miRNAs) are non-coding RNA molecules that influence the development and progression of many diseases. Research have documented that miRNAs have a significant role in the prevention, diagnosis, and treatment of complex human diseases. Recently, scientists have devoted extensive resources to attempting to find the connections between miRNAs and diseases. Since the experimental methods used to discover that new miRNA-disease associations are time-consuming and expensive, many computational methods have been developed. In this research, a novel computational method based on matrix decomposition was proposed to predict new associations between miRNAs and diseases. Furthermore, the nuclear norm minimization method was employed to acquire breast cancer-associated miRNAs. We then evaluated the effectiveness of our method by utilizing two different cross-validation techniques and the results were compared to seven different methods. Moreover, a case study on breast cancer further validated our technique, confirming its predictive accuracy. These experimental results demonstrate that our method is a reliable computational model for uncovering potential miRNA-disease relationships.
Yazarlar (1)
1
Ahmet Toprak
ORCID: 0000-0003-3337-4917
Anahtar Kelimeler
Disease
Matrix decomposition
Matrix nuclear norm
MiRNA
MiRNA-disease associations
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey