Abstract
The continuous advances in genomics, and specifically in the field of transcriptome, require novel computational solutions capable of dealing with great amounts of data. Each expression analysis needs different techniques to explore the data and extract knowledge which allow patients classification. This paper presents a hybrid systems based on Case-based reasoning (CBR) for automatic classification of leukemia patients from Exon array data. The system incorporates novel algorithms for data mining that allow to filter and classify. The system has been tested and the results obtained are presented in this paper.
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
Shortliffe, E.H., Cimino, J.J.: Biomedical Informatics: Computer Applications in Health Care and Biomedicine. Springer, Heidelberg (2006)
Tsoka, S., Ouzounis, C.: Recent developments and future directions in computational genomics. FEBS Letters 480(1), 42–48 (2000)
Lander, E.S., et al.: Initial sequencing and analysis of the human genome. Nature 409, 860–921 (2001)
Rubnitz, J.E., Hijiya, N., Zhou, Y., Hancock, M.L., Rivera, G.K., Pui, C.: Lack of benefit of early detection of relapse after completion of therapy for acute lymphoblastic leukemia. Pediatric Blood & Cancer 44(2), 138–141 (2005)
Affymetrix, GeneChip Human Exon 1.0 ST Array, http://www.affymetrix.com/products/arrays/specific/Exon.affx
Quackenbush, J.: Computational analysis of microarray data. Nature Review Genetics 2(6), 418–427 (2001)
Lipshutz, R.J., Fodor, S.P.A., Gingeras, T.R., Lockhart, D.H.: High density synthetic oligonucleotide arrays. Nature Genetics 21, 20–24 (1999)
Kolodner, J.: Case-Based Reasoning. Morgan Kaufmann, San Francisco (1993)
Irizarry, R.A., Hobbs, B., Collin, F., Beazer-Barclay, Y.D., Antonellis, K.J., Scherf, U., Speed, T.P.: Exploration, Normalization, and Summaries of High density Oligonucleotide Array Probe Level Data. Biostatistics 4, 249–264 (2003)
Kohonen, T.: Self-organized formation of topologically correct feature maps. Biological Cybernetics, 59–69 (1982)
Fritzke, B.: A growing neural gas network learns topologies. Advances in Neural Information Processing Systems 7, 625–632 (1995)
Martinetz, T.: Competitive Hebbian learning rule forms perfectly topology preserving maps. In: ICANN 1993: International Conference on Artificial Neural Networks, pp. 427–434 (1993)
Martinetz, T., Schulten, K.: A neural-gas network learns topologies. In: Kohonen, T., et al. (eds.) Artificial Neural Networks, Amsterdam, pp. 397–402 (1991)
Brunelli, R.: Histogram Analysis for Image Retrieval. Pattern Recognition 34, 1625–1637 (2001)
Gariepy, R., Pepe, W.D.: On the Level sets of a Distance Function in a Minkowski Space. Proceedings of the American Mathematical Society 31(1), 255–259 (1972)
Jolliffe, I.: Principal Component Analysis, 2nd edn. Springer Series in Statistics (2002)
Riverola, F., Díaz, F., Corchado, J.M.: Gene-CBR: a case-based reasoning tool for cancer diagnosis using microarray datasets. Computational Intelligence 22, 254–268 (2006)
Kaufman, L., Rousseeuw, P.J.: Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, New York (1990)
Saitou, N., Nie, M.: The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. 4, 406–425 (1987)
Sneath, P.H.A., Sokal, R.R.: Numerical Taxonomy. The Principles and Practice of Numerical Classication. W.H. Freeman Company, San Francisco (1973)
Fix, E., Hodges, J.L.: Discriminatory analysis, nonparametric discrimination consistency properties, Technical Report 4, United States Air Force, Randolph Field, TX (1951)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Corchado, J.M., De Paz, J.F. (2008). Using CBR Systems for Leukemia Classification. In: Corchado, E., Abraham, A., Pedrycz, W. (eds) Hybrid Artificial Intelligence Systems. HAIS 2008. Lecture Notes in Computer Science(), vol 5271. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87656-4_85
Download citation
DOI: https://doi.org/10.1007/978-3-540-87656-4_85
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87655-7
Online ISBN: 978-3-540-87656-4
eBook Packages: Computer ScienceComputer Science (R0)