Ranking genes for discriminability on microarray data

Journal of Information Science and Engineering

Volumn 19, Issue 6, 2003, Pages 953-966

  Chuang, Han Yu ^a   Tsai, Huai Kuang ^a   Tsai, Yuan Fan ^a   Kao, Cheng Yan ^a  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

Author keywords

Feature selection; Microarray; Ranking based; Support vector machine; Weighted punishment on overlap; Z score

Indexed keywords

DATA STRUCTURES; DISEASES; GENES; INFORMATION ANALYSIS; LEARNING SYSTEMS; TISSUE;

FEATURE SELECTION; MICROARRAY; RANKING-BASED; SUPPORT VECTOR MACHINE; WEIGHTED PUNISHMENT ON OVERLAP; Z-SCORE;

DATA REDUCTION;

EID: 0345529908     PISSN: 10162364     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (15)

1. A. A. Alizadeh, M. B. Eisen, and et al., "Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling," Nature, Vol. 403, 2000, pp. 503-511.
2. U. Alon, N. Barkai, and et al., "Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays," in Proceedings of the National Academy of Sciences, Vol. 96, 1999, pp. 6745-6750.
3. T. R. Golub, D. K. Slonin, and et al., "Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring," Science, Vol. 286, 1999, pp. 531-537.
4. R. Kohavi and G. John, "Wrapper for feature subset selection," Artificial Intelligence, Vol. 97, 1979, pp. 273-324.
5. P. Langley, "Selection of relevant features in machine learning," in Proceedings of the AAAI Fall Symposium on Relevance, AAAI Press, 1994, pp. 140-144.
6. K. Y. Yeung and W. L. Ruzzo, "Principal component analysis for clustering gene expression data," Bioinformatics, Vol. 17, 2001, pp. 763-774.
7. I. Hedenfalk, D. Duggan, Y. Chen, M. Radmacher, M. Bittner, R. Simon, P. Meltzer, B. Gusterson, M. Esteller, O.P. Kallioniemi, B. Wilfond, A. Borg, and J. Trent, "Gene-expression profiles in hereditary breast cancer," New England J. Med., Vol. 8, 2001, pp. 344-539.
8. S. F. Terrence, D. Nigel, and et al., "Support vector machine classification and validation of cancer tissue samples using microarray expression data," Bioinformatics, Vol. 16, 2000, pp. 906-914.
9. A. Ben-Dor, L. Bruhn, and et al., "Tissue classification with gene expression profiles," Journal of Computational Biology, Vol. 7, 2000, pp. 559-583.
10. P. J. Park, M. Pagano, and M. Bonetti, "A nonparametric scoring algorithm for identifying informative genes from microarray data," Pacific Symposium on Biocomputing, Vol. 6, 2001, pp. 52-63.
11. C. C. Chang and C. J. Lin, "LIBSVM: a library for support vector machines, 2001" Software Available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
12. D. A. Notterman, U. Alon, A. J. Sierk, and A. J. Levine, "Transcriptional gene expression profiles of colorectal adenoma, adenocarcinoma, and normal tissue examined by oligonucleotide arrays," Cancer Research, Vol. 61, 2001, pp. 3124-3130.
13. C. Cartes and V. Vapnik, "Support vector machines," Machine Learning, Vol. 20, 1995, pp. 273-297.
14. V. Vapnik, Statistical Learning Theory, John Wiley & Sons, New York, 1999.
15. C. J. C. Burges, "A tutorial on support vector machined for pattern recognition," Data Mining and Knowledge Discovery, Vol. 2, 1998, pp. 121-167.