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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.
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[1] D. P. Bartel, “MicroRNAs: genomics, biogenesis, mechanism, and function”, Cells, 166 (2): 281–297 (2004).
[2] X. Dai et al., “Computational analysis of miRNA targets in plants: current status and challenges”, Briefings Bioinformatics, 12(2), 115-212 (2010).
[3] Y. S. Lee and A. Dutta, “MicroRNAs in cancer”, Annu Rev Pathol, 4, 199-227 (2009).
[4] SM. Hammonad, “microRNA detection comes of age”, Nat Methods, 3(1), 12-13 (2006).
[5] C. G. Liu, “An oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissue”, Proc Natl Acad Sci USA, 101(26), 9740-9744 (2004).
[6] M. V. Iorio et al., “MicroRNA gene expression deregulation in human breast cancer”, Cancer Res, 65(16), 7065-7070 (2005).
[7] H. He et al., “The role of microRNA genes in papillary thyroid carcinoma”, Proc Natl Acad Sci USA, 102(52), 19075-19080 (2005).
[8] G. A. Calin, “Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers”, Proc Natl Acad Sci USA, 101(9), 2999-3004 (2004).
[9] M. V. Iorio et al., “MicroRNA gene expression deregulation in human breast cancer”, Cancer Res, 65(16), 7065-7070 (2005).
[10] S. Volinia et al., “Breast cancer signatures for invasiveness and prognosis defined by deep sequencing of microRNA”, Proc Natl Acad Sci USA, 109(8), 111-114 (2012).
[11] N. Yanaihara et al., Unique microRNA molecular profiles in lung cancer diagnosis and prognosis, Cancer Cell, 9, 189-198 (2006).
[12] Y. Yang et al., The role of microRNA in human lung squamous cell carcinoma, Caner Genet. Cytogenet, 200, 127-133 (2010).
[13] A. Izzotti et al., Chemoprevention of cigarette smoke-induced alterations of MicroRNA expression in rat lungs, Cancer Prev.Res. (Phila, PA), 3, 62-72 (2010).
[14] A. Izztti et al., Modulation of microRNA expression by budesonide phenethyl isothiocyanate and cigarette smoke in mouse liver and lung, Carcinogenesis, 31, 894-901 (2010).
[15] G. Malgorzata et al., MicroRNA-Role in Lung Cancer, Diseas Markers, Article ID 218169, 13 (2014).
[16] A. J. Enright et al., “MicroRNA targets in Drosophila”, Genome Biol, 5(R1) (2003).
[17] B. John et al., “MicroRNA Targets”, PLos Biol, 2(11), e363 (2004).
[18] M. Kertesz et al., “The role of site accessibility in microRNA target recongnition”, Nat. Genet, 39(10), 1278-1284 (2007).
[19] K. Nilubon et al., “Identification of Lung cancer associated protein by Molecular Complex Detection Analysis”, IBBB 2015, Taiwan, Jan. 24- 25 (2015).
[20] A. Bairoch et al., “The Universal Protein Resource (UniProt)”, Nucl.Acids Res, 33, D154-D159 (2005).
[21] G. J. Sam et al., “miRBase: microRNA sequences, targets and gene nomenclature”, Nucl.Acids Res, 34, D140-D144 (2005).
[22] DH. Sheng et al., “miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions”, Nucl. Acids Res, 42(D1), D78-D85 (2014).
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