Prediction of MicroRNA-Target Gene by Machine Learning Algorithms in Lung Cancer Study

MicroRNAs are small non-coding RNA found in
many different species. They play crucial roles in cancer such as
biological processes of apoptosis and proliferation. The identification
of microRNA-target genes can be an essential first step towards to
reveal the role of microRNA in various cancer types. In this paper,
we predict miRNA-target genes for lung cancer by integrating
prediction scores from miRanda and PITA algorithms used as a
feature vector of miRNA-target interaction. Then, machine-learning
algorithms were implemented for making a final prediction. The
approach developed in this study should be of value for future studies
into understanding the role of miRNAs in molecular mechanisms
enabling lung cancer formation.

Authors:

• Nilubon Kurubanjerdjit
• Nattakarn Iam-On
• Ka-Lok Ng

Keywords:

• MicroRNA
• miRNAs
• lung cancer
• machine learning
• Naïve Bayes
• SVM.

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