Scopus
YÖKSİS Eşleşti
Prediction of miRNA-disease associations based on Weighted K-Nearest known neighbors and network consistency projection
Journal of Bioinformatics and Computational Biology · Şubat 2021
YÖKSİS Kayıtları
Prediction of miRNA-disease associations based on Weighted K-Nearest known neighbors and network consistency projection
Journal of Bioinformatics and Computational Biology · 2021 SCI-Expanded
DOÇENT ESMA ERYILMAZ DOĞAN →
Prediction of miRNA-disease associations based on Weighted K-Nearest known neighbors and network consistency projection
JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY · 2021 SCI-Expanded
DOÇENT AHMET TOPRAK →
Makale Bilgileri
DergiJournal of Bioinformatics and Computational Biology
Yayın TarihiŞubat 2021
Cilt / Sayfa19
Scopus ID2-s2.0-85095789408
Özet
MicroRNAs (miRNA) are a type of non-coding RNA molecules that are effective on the formation and the progression of many different diseases. Various researches have reported that miRNAs play a major role in the prevention, diagnosis, and treatment of complex human diseases. In recent years, researchers have made a tremendous effort to find the potential relationships between miRNAs and diseases. Since the experimental techniques used to find that new miRNA-disease relationships are time-consuming and expensive, many computational techniques have been developed. In this study, Weighted K-Nearest Known Neighbors and Network Consistency Projection techniques were suggested to predict new miRNA-disease relationships using various types of knowledge such as known miRNA-disease relationships, functional similarity of miRNA, and disease semantic similarity. An average AUC of 0.9037 and 0.9168 were calculated in our method by 5-fold and leave-one-out cross validation, respectively. Case studies of breast, lung, and colon neoplasms were applied to prove the performance of our proposed technique, and the results confirmed the predictive reliability of this method. Therefore, reported experimental results have shown that our proposed method can be used as a reliable computational model to reveal potential relationships between miRNAs and diseases.
Yazarlar (2)
1
Ahmet Toprak
ORCID: 0000-0003-3337-4917
2
Esma Eryilmaz Dogan
Anahtar Kelimeler
disease
MiRNA
miRNA-disease association
network consistency projection
similarity measure
weighted K-nearest known neighbors
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
4
Atıf
2
Yazar
6
Anahtar Kelime