MicroRNA prediction based on 3D graphical representation of RNA secondary structures

Müşerref Duygu SAÇAR DEMİRCİ

Makale detayları

MicroRNA prediction based on 3D graphical representation of RNA secondary structures

Yazarlar:

Müşerref Duygu SAÇAR DEMİRCİ

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Biology 2019 Vol.43 Issue 4, pp.274-280

Belge Tipi:

Makale

Yayın Tarihi:

8/2019

Belge Dili:

İngilizce

Document ID (Org No.):

2000811100

Sıklık:

İki Aylık

eISSN:

1303-6092

pISSN:

1300-0152

Özet:

 

MicroRNAs (miRNAs) are posttranscriptional regulators of gene expression. While a miRNA can target hundreds of messenger RNA (mRNAs), an mRNA can be targeted by different miRNAs, not to mention that a single miRNA might have various binding sites in an mRNA sequence. Therefore, it is quite involved to investigate miRNAs experimentally. Thus, machine learning (ML) is frequently used to overcome such challenges. The key parts of a ML analysis largely depend on the quality of input data and the capacity of the features describing the data. Previously, more than 1000 features were suggested for miRNAs. Here, it is shown that using 36 features representing the RNA secondary structure and its dynamic 3D graphical representation provides up to 98% accuracy values. In this study, a new approach for ML-based miRNA prediction is proposed. Thousands of models are generated through classification of known human miRNAs and pseudohairpins with 3 classifiers: decision tree, naïve Bayes, and random forest. Although the method is based on human data, the best model was able to correctly assign 96% of nonhuman hairpins from MirGeneDB, suggesting that this approach might be useful for the analysis of miRNAs from other species.

Makale detayları

MicroRNA prediction based on 3D graphical representation of RNA secondary structures

Yazarlar: Müşerref Duygu SAÇAR DEMİRCİ

Yayıncı: TUBITAK

Dergi: Turkish Journal of Biology 2019 Vol.43 Issue 4, pp.274-280

Belge Tipi: Makale

Yayın Tarihi: 8/2019

Belge Dili: İngilizce

Document ID (Org No.): 2000811100

Sıklık: İki Aylık

eISSN: 1303-6092

pISSN: 1300-0152

Sayı

Yazarlar:

Müşerref Duygu SAÇAR DEMİRCİ

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Biology 2019 Vol.43 Issue 4, pp.274-280

Belge Tipi:

Makale

Yayın Tarihi:

8/2019

Belge Dili:

İngilizce

Document ID (Org No.):

2000811100

Sıklık:

İki Aylık

eISSN:

1303-6092

pISSN:

1300-0152