Correlation-based scatter search for discovering biclusters from gene expression data

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

Volumn 6023 LNCS, Issue , 2010, Pages 122-133

  Nepomuceno, Juan A ^a   Troncoso, Alicia ^b   Aguilar Ruiz, Jesús S ^b  

^a UNIVERSITY OF SEVILLE   (Spain)

^b UNIVERSIDAD PABLO DE OLAVIDE   (Spain)

Author keywords

Biclustering; Evolutionary Computation; Gene Expression Data; Scatter Search

Indexed keywords

BIOINFORMATICS; CALCULATIONS; EVOLUTIONARY ALGORITHMS; GENE EXPRESSION; GENETIC ALGORITHMS; MACHINE LEARNING;

BI-CLUSTERING; BIOLOGICAL POINTS; EVOLUTIONARY METHOD; GENE EXPRESSION DATA; IMPROVEMENT METHODS; LINEAR CORRELATION; SCATTER SEARCH; YEAST CELL CYCLES;

DATA MINING;

EID: 77952313200     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-12211-8_11     Document Type: Conference Paper

References (18)

1. Larranaga, P., et al.: Machine learning in bioinformatics. Briefings in Bioinformatics 7(1), 86-112 (2006)
2. Busygin, S., Prokopyev, O., Pardalos, P.: Biclustering in data mining. Computers and Operations Research 35(9), 2964-2987 (2008)
3. Getz, G., Levine, E., Domany, E.: Couple two-way clustering analysis of gene microarray data. In: Proceedings of the National Academy of Sciences (PNAS) of the USA, pp. 12079-12084 (2000)
4. Cheng, Y., Church, G.: Biclustering of Expression Data. In: Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, vol.8, pp. 93-103 (2000)
5. Tanay, A., Sharan, R., Shamir, R.: Discovering statistically significant biclusters in gene expression data. Bioinformatics 18(90001), 136-144 (2002)
6. Yang, J., Wang, H., Wang, W., Yu, P.: Enhanced biclustering on expression data. In: 3rd IEEE Simposium on Bioinformatics and Bioengeneering, pp. 321-327 (2003)
7. Bergmann, S., Ihmels, J., Barkai, N.: Iterative signature algorithm for the analysis of large-scale gene expression data. Physical Review E 67(031902) (2003)
8. Divina, F., Aguilar-Ruiz, J.: Biclustering of Expression Data with Evolutionary Computation. IEEE Transactions on Knowledge and Data Engineering 18(5), 590-602 (2006)
9. Mitra, S., Banka, H.: Multi-objective evolutionary biclustering of gene expression data. Pattern Recognition 39(12), 2464-2477 (2006) (Pubitemid 44344744)
10. Bryan, K.: Biclustering of Expression Data Using Simulated Annealing. In: Proceedings of the 18th IEEE International Symposium on Computer-Based Medical Systems, USA, pp. 383-388 (2005)
11. Aguilar-Ruiz, J.: Shifting and scaling patterns from gene expression data. Bioinformatics 21(20), 3840-3845 (2005)
12. Harpaz, R., Haralick, R.: Mining Subspace Correlations. In: IEEE Symposium on Computational Intelligence and Data Mining, pp. 335-342 (2007)
13. Zhao, H., Liew, A., Xie, X., Yan, H.: A new geometric biclustering algorithm based on the Hough transform for analysis of large-scale microarray data. Journal of Theoretical Biology 251(2), 264-274 (2008)
14. Gan, X., Liew, A., Yan, H.: Discovering biclusters in gene expression data based on high-dimensional linear geometries. BMC Bioinformatics 9(209), 1-15 (2008)
15. Nepomuceno, J.A., Troncoso Lora, A., Aguilar-Ruiz, J.S., García-Gutiérrez, J.: Biclusters Evaluation Based on Shifting and Scaling Patterns. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds.) IDEAL 2007. LNCS, vol.4881, pp. 840-849. Springer, Heidelberg (2007)
16. Marti, R., Laguna, M.: Scatter Search. In: Methodology and Implementation in C. Kluwer Academic Publishers, Boston (2003)
17. Alizadeh, A., et al.: Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403, 503-511 (2000)
18. Cho, R., et al.: A Genome-Wide Transcriptional Analysis of the Mitotic Cell Cycle. Molecular Cell 2(1), 65-73 (1998)