Cluster validation techniques for genome expression data

Signal Processing

Volumn 83, Issue 4, 2003, Pages 825-833

  Bolshakova, N ^a   Azuaje, F ^b  

^a TRINITY COLLEGE DUBLIN   (Ireland)

^b UNIVERSITY OF ULSTER   (United Kingdom)

Author keywords

Cluster validation; Clustering; Genome expression; Genomic data mining

Indexed keywords

ALGORITHMS; DATA REDUCTION; PERTURBATION TECHNIQUES; PROBLEM SOLVING;

CLUSTER VALIDATION TECHNIQUES;

GENES;

EID: 0037399775     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-1684(02)00475-9     Document Type: Article

References (25)

1. Alizadeh A.A., Eisen M.B., Davis R.E., Ma C., Lossos I.S., Rosenwald A., Boldrick J.C., Sabet H., Tran T., Yu X., Powell J.I., Yang L., Marti G.E., Moore T., Hudson J., Lu L., Lewis D.B., Tibshirani R., Sherlock G., Chan W.C., Greiner T.C., Weisenburger D.D., Armitage J.O., Warnke R., Levy R., Wilson W., Grever M.R., Bird J.C., Botstein D., Brown P.O., Staudt M. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 403:2000;503-511.
2. Ambroise C., McLachlan G.J. Selection bias in gene extraction on basis of microarray gene expression data. Proc. Nat. Acad. Sci. USA. 99:2002;6562-6566.
3. Azuaje F. A computational neural approach to support the discovery of gene function and classes of cancer. IEEE Trans. Biomed. Eng. 48:2001;332-339.
4. Azuaje F. A cluster validity framework for genome expression data. Bioinformatics. 18:2002;319-320.
5. F. Azuaje, N. Bolshakova, Clustering genome expression data: design and evaluation principles, in: D. Berrar, W. Dubitzky, M. Granzow (Eds.), Understanding and Using Microarray Analysis Techniques: A Practical Guide, Springer, London, 2002, in press.
6. Berns A. Cancer. gene expression in diagnosis Nature. 403:2000;491-492.
7. Bezdek J.C., Pal N.R. Some new indexes of cluster validity. IEEE Trans. Systems, Man Cybernet. B. 28:1998;301-315.
8. Bittner M., Meltzer P., Chen Y., Jiang Y., Seftor E., Hendrix M., Radmacher M., Simon R., Yakhini Z., Ben-Dor A., Sampas N., Dougherty E., Wang E., Marincola F., Gooden C., Lueders J., Glatfelter A., Pollock P., Carpten J., Gillanders E., Leja D., C. Beaudry Dietrich, Berens M., Alberts D., Sondak V., Hayward N., Trent J. Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature. 406:2000;536-540.
9. N. Bolshakova, F. Azuaje, Improving expression data mining through cluster validation, Fourth Annual IEEE EMBS Special Topic Conference on Information Technology Applications in Biomedicine, 2003, submitted for publication.
10. Davies D.L., Bouldin D.W. A cluster separation measure. IEEE Trans. Pattern Recognition Machine Intell. 1(2):1979;224-227.
11. Dunn J. Well separated clusters and optimal fuzzy partitions. J. Cybernet. 4:1974;95-104.
12. K. Dunne, P. Cunningham, F. Azuaje, Solutions to instability problems with sequential wrapper-based approaches to feature selection, J. Machine Learning Res. 2002, submitted for publication.
13. Everitt B. Cluster Analysis. 1993;Edward Arnold, London.
14. Golub T.R., Slonim D.K., Tamayo P., Huard C., Gassenbeck M., Mesirov J.P., Coller H., Loh M.L., Downing J.R., Caligiuri M.A., Bloomfield C.D., Lander E.S. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science. 286:1999;531-537.
15. Goodman L., Kruskal W. Measures of associations for cross-validations. J. Am. Stat. Assoc. 49:1954;732-764.
16. Granzow M., Berrar D., Dubitzky W., Schuster A., Azuaje F., Eils R. Tumor identification by gene expression profiles. a comparison of five different clustering methods ACM-SIGBIO Newsletters. 21:2001;16-22.
17. S. Gunter, H. Burke, Validation indices for graph clustering, in: J.-M. Jolion, W. Kropatsch, M. Vento (Eds.), Proceedings of the 3rd IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition, 2001, pp. 229-238.
18. Halkidi M., Batistakis Y., Vazirgiannis M. On clustering validation techniques. JIIS. 17:2001;107-145.
19. Hubert L.J., Arabie P. Comparing partitions. J. Classification. 2:1985;193-218.
20. Hubert L., Schultz J. Quadratic assignment as a general data-analysis strategy. Br. J. Math. Statist. Psychol. 29:1976;190-241.
21. Quackenbush J. Computational analysis of microarray data. Nature Review. 2:2001;418-427.
22. Rousseeuw P.J. Silhouettes. a graphical aid to the interpretation and validation of cluster analysis J. Comput. Appl. Math. 20:1987;53-65.
23. Schena M., Shalon D., Davis R.W., Brown P.O. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science. 270:1995;467-470.
24. Singh D., Febbo P.G., Ross K., Jackson D.G., Manola J., Ladd C., Tamayo P., Renshaw A.A., D'Amico A.V., Richie J.P., Lander E.S., Loda M., Kantoff P.W., Golub T.R., Sellers W.R. Gene expression correlates of clinical prostate cancer behavior. Cancer Cell. 1:2002;203-209.
25. Yeung K.Y., Haynor D.R., Ruzzo W.L. Validating clustering for gene expression data. Bioinformatics. 17:2001;309-318.