%0 Journal Article
	%A Nilubon Kurubanjerdjit and  Nattakarn Iam-On and  Ka-Lok Ng
	%D 2016
	%J International Journal of Medical and Health Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 110, 2016
	%T Prediction of MicroRNA-Target Gene by Machine Learning Algorithms in Lung Cancer Study
	%U https://publications.waset.org/pdf/10003520
	%V 110
	%X 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.
	%P 52 - 55