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Title: Polyadenylation Site Prediction Using Interesting Emerging Pattern
Author(s): G. Tzanis, I. Kavakiotis, I. Vlahavas.
Availability: Click here to download the PDF (Acrobat Reader) file (6 pages).
Keywords: prediction, polyadenylation, mRNA, messanger RNA, emerging patterns, data mining, Arabidopsis thaliana.
Appeared in: 8th IEEE International Conference on Bioinformatics and Bioengineering, IEEE, Athens, Greece, 2008.
Abstract: This paper presents a study on polyadenylation site prediction in mRNA sequences. We describe a method, called PolyA-EP, that we developed for predicting polyadenylation sites and we present a systematic study of the problem of recognizing mRNA 3΄ ends which contain a polyadenylation site using the proposed method. PolyA-EP exploits the advantages of emerging patterns, namely high understandability and discriminating power and can be used for both descriptive and predictive analysis. In particular, PolyA-EP is a parameterizable tool that can be used in order to extract interesting emerging patterns for describing or predicting polyadenylation sites. Moreover, the extracted emerging patterns can span across many elements around the polyadenylation site. We discuss the results of the experiments we conducted with Arabidopsis thaliana sequences drawing important conclusions and finally we propose a framework that improves the accuracy of polyadenylation site prediction.
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1 Liu, S.-K. (2010). Prediction of mRNA polyadenylation sites in human genes by nucleotide composition. Master Thesis, Department of Computer Science and Information Engineering, National Central University, Taiwan.
2 Horng, J.-T., Wu, L.-C., Liu, S.-K., Chang, C.-W., Chao, T.-M., Yeh, R.-H., and Cheng, K.-F. (2011). A Prediction of mRNA Polyadenylation Sites in Human Genes. In Pro-ceedings of the 11th IEEE International Conference on Bioinformatics and Bioengineering, pp.27-32.
3 Contrast Data Mining: Concepts, Algorithms, and Applications, Chapman & Hall/CRC Data Mining and Knowledge Discovery Series, Guozhu Dong (Editor), James Bailey (Editor) (2012)
4 Ho, E.S., Gunderson, S.I., and Duffy, S. (2013). A multispecies polyadenylation site model. BMC Bioinformatics, 14(Suppl 2):S9.
5 Ji G, Guan J, Zeng Y, Li QQ, Wu X. (2014) Genome-wide identification and predictive modeling of polyadenylation sites in eukaryotes.Brief Bioinform (2014) Apr 1. doi: 10.1093/bib/bbu011