Abstract
It is estimated that 40-60% of human genes undergo alternative splicing. Currently, expressed sequence tags (ESTs) alignment and microarray analysis are the most efficient methods for large-scale detection of alternative splice events. Because of the inherent limitation of these methods, it is hard to detect retained introns using them. Thus, it is highly desirable to predict retained introns using only their own sequence information. In this paper, support vector machine is introduced to predict retained introns merely based on their own sequences. It can achieve a total accuracy of 98.54%. No other data, such as ESTs, are required for the prediction. The results indicate that support vector machine can achieve a reasonable acceptant prediction performance for retained introns with effective rejection of constitutive introns.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Graveley, B.R.: Alternative Splicing: Increasing Diversity in the Proteomic World. Trends Genet. 17(2), 100–107 (2001)
Modrek, B., Lee, C.: A Genomic View of Alternative Splicing. Nat. Genet. 30(1), 13–19 (2002)
Galante, P.A., Sakabe, N.J., Kirschbaum-Slager, N., de Souza, S.J.: Detection and Evaluation of Intron Retention Events in the Human Transcriptome. RNA 10(5), 757–765 (2004)
Michael, I.P., Kurlender, L., Memari, N., et al.: Intron Retention: a Common Splicing Event within the Human Kallikrein Gene Family. Clin. Chem. 51(3), 506–515 (2005)
Johnson, J.M., Castle, J., Garrett-Engele, P., et al.: Genome-Wide Survey of Human Alternative Pre-mRNA Splicing with Exon Junction Microarrays. Science 302(5653), 2141–2144 (2003)
Hiller, M., Huse, K., Platzer, M., Backofen, R.: Non-EST Based Prediction of Exon Skipping and Intron Retention Events Using Pfam Information. Nucleic Acids Res. 33(17), 5611–5621 (2005)
Thanaraj, T.A., Stamm, S., Clark, F., Riethoven, J.J., Le Texier, V., Muilu, J.: ASD: the Alternative Splicing Database. Nucleic Acids Res. 32(Database Issue), D64–D69 (2004)
Wen, F., Li, F., Xia, H.Y., Lu, X., Zhang, X.G., Li, Y.D.: The Impact of Very Short Alternative Splicing on Protein Structures and Functions in the Human Genome. Trends Genet. 20(5), 232–236 (2004)
Norton, P.A.: Polypyrimidine Tract Sequences Direct Selection of Alternative Branch Sites and Influence Protein Binding. Nucleic Acids Res. 22(19), 3854–3860 (1994)
Kol, G., Lev-Maor, G., Ast, G.: Human-Mouse Comparative Analysis Reveals that Branch-Site Plasticity Contributes to Splicing Regulation. Hum. Mol. Genet. 14(11), 1559–1568 (2005)
Vapnik, V.N.: Statistical Learning Theory. Wiley, New York (1998)
Dror, G., Sorek, R., Shamir, R.: Accurate Identification of Alternatively Spliced Exons Using Support Vector Machine. Bioinformatics 21(7), 897–901 (2005)
Joachims, T.: Making Large-Scale SVM Learning Practical. In: Schölkopf, B., Burges, C., Smola, A. (eds.) Advances in Kernel Methods - Support Vector Learning, Ch.11, pp. 169–184. MIT Press, Cambridge (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Xia, H., Bi, J., Li, Y. (2006). Support Vector Machine Approach for Retained Introns Prediction Using Sequence Features. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_96
Download citation
DOI: https://doi.org/10.1007/11760191_96
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34482-7
Online ISBN: 978-3-540-34483-4
eBook Packages: Computer ScienceComputer Science (R0)