Biclustering of microarray data based on singular value decomposition

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

Volumn 4819 LNAI, Issue , 2007, Pages 194-205

  Yang, Wen Hui ^a   Dai, Dao Qing ^a,b   Yan, Hong ^b,c  

^a SUN YAT SEN UNIVERSITY   (China)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^c UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

BIOACTIVITY; CLUSTERING ALGORITHMS; DATA STRUCTURES; GENE EXPRESSION; MICROARRAYS; SINGULAR VALUE DECOMPOSITION;

BICLUSTER PROBLEMS; GLOBAL CLUSTERING PROBLEMS;

BIOINFORMATICS;

EID: 38549091010     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-77018-3_21     Document Type: Conference Paper

References (22)

1. Abdullah, A., Hussain, A., et al.: A new biclustering technique based on crossing minimization. Neurocomputing 69, 1882-1896 (2006)
2. Alizadeh, A.A., Eisen, M.B., et al.: Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403, 503-511 (2000)
3. Alter, O., Brown, P.O., Botstein, D.: Singular value decomposition for genome-wide expression data processing and modeling. Proceedings of the National Academy of Sciences 97(18), 10101-10106 (2000)
4. Alter, O., Golub, G.H.: Singular value decomposition of genome-scale mrna lengths distribution reveals asymmetry in ma gel electrophoresis band broadening. Proceedings of the National Academy of Sciences 103(32), 11828-11833 (2006)
5. Ben-Dor, A., Chor, B., Karp, R., Yakhini, Z.: Discovering local structure in gene expression data: the order-preserving sub-matrix problem. In: Proceedings of the 6th Annual International Conference on Computational Biology (RECOMB 2002), New York, USA, pp. 49-57 (2002)
6. Carmona-Saez, P., Pascual-Marqui, R.D., Tirado, F., Carazo, J.M., Pascual-Montano, A.: Biclustering of gene expression data by non-smooth non-negative matrix factorization. BMC Bioinformatics 7(78) (2006)
7. Changdra, B., Shanker, S., Mishra, S.: A new approach: Interrelated two-way clustering of gene expression data. Statistical Methodology 3, 93-102 (2006)
8. Cheng, Y., Church, G.M.: Biclustering of gene expression data. In: Proc. 8th Int. Conf. Intelligent Systems for Molecular Biology (ISMB 2000), San Diego, CA, pp. 93-103 (2000)
9. Dudoit, S., Fridlyand, J., Speed, T.: Comparison of discrimination methods for the classification of tumors using gene expression data. Journal of the American Statistical Association 97, 77-87 (2002)
10. Hartigan, J.A.H.: Direct clustering of a data matrix. Journal of the American Statistical Association 67(337), 123-129 (1972)
11. Ihmels, J., Bergmann, S., Barkai, N.: Defining transcription modules using large-scale gene expression data. Bioinformatics 20, 1993-2003 (2004)
12. Jackson, D.A.: Stopping rules in principal components analysis: a comparison of heuristical and statistical approaches. Ecology 74, 2204-2214 (1993)
13. Kluger, Y., Basri, R., Chang, J.T., Gerstein, M.: Spectral biclustering of microarraydata: coclustering genes and conditions. Genome Research 13(4), 703-716 (2003)
14. Lazzeroni, L., Owen, A.: Plaid models for gene expression data. Statistica Sinica 12(1), 61-86 (2002)
15. Liu, B., Wan, C., Wang, L.: An efficient semi-unsupervised gene selection method via spectral biclustering. IEEE Transactions on Nanobioscience 5(2), 110-114 (2006)
16. Liu, L., Hawkins, D.M., Ghosh, S., Young, S.S.: Robust singular value decomposition analysis of microarray data. Proceedings of the National Academy of Sciences 100(23), 13167-13172 (2003)
17. Madeira, S.C., Oliveira, A.L.: Biclustering algorithms for biological data analysis: a survey. IEEE/ACM Transactions on Computational Biology and Bioinformatics 1(1), 24-45 (2004)
18. McLachlan, G., Do, K., Ambroise, C.: Analysing microarray gene expression data. Wiley, Chichester (2004)
19. Mirkin, B.: Mathematical Classification and Clustering. Kluwer Academic Press, Norwell (1996)
20. Pomeroy, S.L., Tamayo, P., et al.: Prediction of central nervous system embryonal tumour outcome based on gene expression. Nature 24(415), 436-442 (2002)
21. Tanay, A., Sharan, R., Shamir, R.: Discovering statistically significant biclusters in gene expression data. Bioinformatics 18, 36-44 (2002)
22. Yang, W.H., Dai, D.Q., Yan, H.: Generalized discriminant analysis for tumor classification with gene expression data. In Proceedings of the Fifth International Conference on Machine Learning and Cybernetics (ICMLC 2006), pp. 4322-4327, Dalian, China (2006)