Two-stage classification methods for microarray data

Expert Systems with Applications

Volumn 34, Issue 1, 2008, Pages 375-383

  Wong, Tzu Tsung ^a   Hsu, Ching Han ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Dimension reduction; Gene selection; Microarray data; Two stage classification method

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA ACQUISITION; DIAGNOSIS; DISEASES; GENE EXPRESSION;

DIMENSION REDUCTION; GENE SELECTION; MICROARRAY DATA; TWO-STAGE CLASSIFICATION METHOD;

MICROARRAYS;

EID: 34248550574     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2006.09.005     Document Type: Article

References (22)

1. Albrecht A., Vintwebo S.A., and Ohno-Machado L. An Epicurean learning approach to gene-expression data classification. Artificial Intelligence in Medicine 28 (2003) 75-87
2. Antoniadis A., Lambert-Lacroiix S., and Leblance F. Effective dimension reduction methods for tumor classification using gene expression data. Bioinformatics 19 (2003) 563-570
3. Asyali M.H., and Alci M. Reliability analysis of microarray data using fuzzy c-means and normal mixture modeling based classification methods. Bioinformatics 21 (2005) 644-649
4. Desper R., Khan J., and Schäffer A.A. Tumor classification using phylogenetic methods on expression data. Journal of Theoretical Biology 228 (2004) 477-496
5. Dudoit S., Fridlyand J., and Speed T. Comparison of discrimination methods for the classification of tumor using gene expression data. Journal of the American Statistical Association 97 (2002) 77-87
6. Friedman N., Linial M., Nachman I., and Pe'er D. Using Bayesian networks to analyze expression data. Journal of Computational Biology 7 (2000) 601-620
7. Georgii E., Richter L., Ruckert U., and Kramer S. Analyzing microarray data using quantitative association rules. Bioinformatics 21 (2005) 123-129
8. Golub T.R., Slonim D.K., Tamayo P., Huard C., Gaasenbeek M., Mesirov J.P., et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286 (1999) 531-537
9. Jörnsten R., and Yu B. Simultaneous gene clustering and subset selection for sample classification via MDL. Bioinformatics 19 (2003) 1100-1109
10. Khan J., Wei J.S., Ringnér M., Saal L.H., Ladanyi M., Westermann F., et al. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nature Medicine 7 (2001) 673-679
11. Lee K.E., Sha N., Dougherty E.R., Vannucci M., and Mallick B.K. Gene selection: a Bayesian variable selection approach. Bioinformatics 19 (2003) 90-97
12. Li L., Weinberg R.C., Darden T.A., and Pedersen L.G. Gene selection for sample classification based on gene expression data: study of sensitivity to choice of parameters of the GA/KNN method. Bioinformatics 17 (2001) 1131-1142
13. Lu Y., and Han J. Cancer classification using gene expression data. Information Systems 28 (2003) 243-268
14. Martella F. Classification of microarray data with factor mixture models. Bioinformatics 22 (2006) 202-208
15. Mitchell T.M. Machine Learning (1997), McGraw Hill
16. Nguyen D.V., and Rocke D.M. Tumor classification by partial least squares using microarray gene expression data. Bioinformatics 18 (2002) 39-50
17. Park P., Pagano M., and Bonetti M. A nonparametric scoring algorithm for identifying informative genes from microarray data. Proceedings of the Pacific Symposium on Biocomputing 6 (2001) 52-63
18. Qiu P., Wang Z.J., and Liu K.J.R. Ensemble dependence model for classification and prediction of cancer and normal gene expression data. Bioinformatics 21 (2005) 3114-3121
19. Quackenbush J. Computational analysis of microarray data. Nature Review Genetic 2 (2001) 418-427
20. Simek K., Fujarewicz K., Swierniak A., Kimmel M., Jarzab B., Wiench M., et al. Using SVD and SVM methods for selection, classification, clustering and modeling of DNA microarray data. Engineering Application of Artificial Intelligence 17 (2004) 417-427
21. Wu B.L. Differential gene expression detection and sample classification using penalized linear regression models. Bioinformatics 22 (2006) 472-476
22. Zhang H., Yu C., Singer B., and Xiong M. Recursive partitioning for tumor classification with gene expression microarray data. Proceedings of the National Academy Sciences of the United States of America 98 (2001) 6730-6735