Gene selection using Wilcoxon rank sum test and support vector machine for cancer classification

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4456 LNAI, Issue , 2007, Pages 57-66

  Liao, Chen ^a   Li, Shutao ^a   Luo, Zhiyuan ^b  

^a HUNAN UNIVERSITY   (China)

^b UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA PROCESSING; GENE EXPRESSION; MICROARRAYS; SUPPORT VECTOR MACHINES;

GENE SELECTION; LEUKEMIA; WILCOXON RANK SUM TESTS;

TUMORS;

EID: 38349055168     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74377-4_7     Document Type: Conference Paper

References (15)

1. Liu, H., Li, J., Wong, L.: A Comparative Study on Feature Selection and Classification Methods using Gene Expression Profiles and Proteomic Patterns. Genome Information 13, 51-60 (2002)
2. Liu, H., Li, J., Wong, L.: Selection of Patient Samples and Genes for Outcome Prediction. In: Proceedings of the IEEE Computational Systems Bioinformatics Conference, Stanford, pp. 382-392. IEEE Computer Society Press, Los Alamitos (2004)
3. Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines. Cambridge University Press, Cambridge (2000)
4. Guyon, I., Weston, J., Barnhill, S., Vapnik, V.: Gene Selection for Cancer Classification using Support Vector Machines. Machine Learning 46, 389-422 (2002)
5. Zhang, X., Wong, W.: Recursive Sample Classification and Gene Selection Based on SVM: Method and Software Description. In: Technical Report, Department of Biostatistics, Harvard School of Public Health, USA (2001)
6. Furlanello, C., Serafini, M., Merler, S., Jurman, G.: An Accelerated Procedure for Recursive Feature Ranking on Microarray Data. Neural Networks 16, 641-648 (2003)
7. Tang, Y., Zhang, Y., Huang, Z.: FCM-SVM-RFE Gene Feature Selection Algorithm for Leukemia Classification from Microarray Gene Expression Data. In: Proceedings of the IEEE International Conference on Fuzzy Systems, pp. 97-101. IEEE Computer Society Press, Los Alamitos (2005)
8. Duan, K., Rajapakse, J.C.: A Variant of SVM-RFE for Gene Selection in Cancer Classification with Expression Data. In: Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, San Diego, pp. 49-55. IEEE Computer Society Press, Los Alamitos (2004)
9. Duan, K., Rajapakse, J.C, Haiying, W., Azuaje, F.: Multiple SVM-RFE for Gene Selection in Cancer Classification with Expression Data. IEEE Transactions on Nanobioscience 4, 228-233 (2005)
10. West, M., Blanchette, C., Dressman, H., et al.: Predicting the Clinical Status of Human Breast Cancer Using Gene Expression Profiles. In: Proceedings of the National Academy of Science, vol. 98, pp. 11462-11467 (2001)
11. Golub, T., Slonim, D., Tamayo, P., et al.: Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring. Science 28, 531-537 (1999)
12. Krishnapuram, B., Carin, L., Hartemink, A.: Gene expression analysis: Joint Feature Selection and Classifier Design. In: Schölkopf, B., Tsuda, K., Vert, J-P (eds.) Kernel Methods in Computational Biology, Schölkopf, B, pp. 299-317. MIT Press, Cambridge, MA (2004)
13. Ben-Dor, A., Bruhn, L., Friedman, N. et al.: Tissue Classification with Gene Expression Profiles. Journal of Computational Biology 7, 559-583 (2000)
14. Li, Y., Campbell, C., Tipping, M.: Bayesian Automatic Relevance Determination Algorithms for Classifying Gene Expression Data. Bioinformatics 18, 1332-1339 (2002)
15. Figueiredo, M., Jain, A.: Bayesian Learning of Sparse Classifiers. In: Proceedings of International Conference on Computer Vision and Pattern Recognition, Wisconsin, pp. 35-41 (2001)