Efficient bisecting k-medoids and its application in gene expression analysis

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

Volumn 5112 LNCS, Issue , 2008, Pages 423-434

  Kashef, Rasha ^a   Kamel, Mohamed S ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Bisecting clustering; Clustering; Quality measures

Indexed keywords

GENE EXPRESSION ANALYSIS; INTERNATIONAL CONFERENCES; K MEANS; K-MEDOIDS; MEDOIDS; NOISY DATA; SMALL CLUSTERS;

ARCHITECTURAL ACOUSTICS; ASSOCIATIVE STORAGE; GENE EXPRESSION; IMAGE ANALYSIS; IMAGING TECHNIQUES; PARTITIONS (BUILDING); PNEUMATIC DRIVES; PULSE AMPLITUDE MODULATION;

CLUSTERING ALGORITHMS;

EID: 47849118379     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-69812-8_42     Document Type: Conference Paper

References (22)

1. Hartigan, J.: Clustering Algorithms, Wiley Series in Probability and Mathematical Statistics (1975)
2. Jain, A., Murty, M., Flynn, P.: Data Clustering: A Review. ACM computing surveys 31, 264-323 (1999)
3. Ben-Dor, A., Shamir, R., Yakhini, Z.: Clustering gene expression patterns. Journal of Computational Biology 6(3/4), 281-297 (1999)
4. Shamir, R., Sharan, R.: Algorithmic Approaches to Clustering Gene Expression Data. In: Current Topics in Computational Biology, pp. 269-299. MIT Press, Cambridge (2002)
5. Hartuv, E., Shamir, R.: A clustering algorithm based on graph connectivity. Information Processing Letters 76(200), 175-181 (2000)
6. Hartigan, J., Wong, M.: A k-means Clustering Algorithm. Applied Statistics 28, 100-108 (1979)
7. Bezdek, J., Ehrlich, R., Full, W.: The Fuzzy C-Means Clustering Algorithm. Computers and Geosciences 10, 191-203 (1984)
8. Savaresi, S., Boley, D.: On the Performance of Bisecting K-means and PDDP. In: Proc. of the 1st SIAM Int. Conf. on Data Mining, pp. 1-14 (2001)
9. Yousri, N.A., Ismail, M.A., Kamel, M.S.: Discovering Connected Patterns in Gene Expression Arrays. In: IEEE Symposium on Computational intelligence and Bioinformatics and Computational Biology (CIBCB), pp. 113-120 (2007)
10. Lu, Y., Lu, S., Fotouhi, F., Deng, Y., Brown, S.: Incremental Genetic K-means Algorithm and its Application in Gene Expression Data Analysis. BMC Bioinformatics 5(172) (2004)
11. Golub, T., Slonim, D., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J., Coller, H., Loh, M., Downing, J., Caligiuri, M.A., Bloomfield, C., Lander, E.: Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring. Science 286(5439), 531-537 (1999)
12. Monti, S., Tamayo, P., Mesirov, J., Golub, T.: Consensus Clustering: A resampling-based method for class discovery and visualization of gene expression microarray data. Kluwer Academic Publishers, Dordrecht (2003)
13. Kaufmann, L., Rousseeuw, P.: Finding groups in data. Wiley, Chichester (1990)
14. Kustra, R., Zaganski, A.: Incorporating Gene Ontology in Clustering Gene Expression Data. In: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems, pp. 555-563 (2006)
15. Ng, R.T., Han, J.: Efficient and effective clustering methods for spatial data mining. In: VLDB, pp. 144-155 (1994)
16. Hammouda, K., Kamel, M.: Collaborative Document Clustering. In: SIAM Conference on Data Mining (SDM 2006), pp. 453-463 (2006)
17. Zhao, Y., Karypis, G.: Criterion Functions for Document Clustering: Experiments and Analysis, Technical report, Department of Computer Science,University of Minnesota, Minneapolis, MN (2002)
18. Bensaid, A., Hall, L.O., Bezdek, J., Clarke, L., Silbiger, M., Arrington, J., Murtagh, R.: Validity-guided (Re)Clustering with applications to imige segmentation. IEEE Transactions on Fuzzy Systems, 112-123 (1996)
19. Tavazoie, S., Hughes, J., Campbell, M., Cho, R., Church, G.: Systematic determination of genetic network architecture. Nature Genetics 22, 281-285 (1999)
20. West, M., Blanchette, C., Dressman, H., Huang, E., Ishida, S., Spang, R., Zuzan, H., Olson, J., Marks, J., Nevins, J.: Predicting the clinical status of human breast cancer by using gene expression profiles. Proc. Natl. Acad. Sci. USA 98, 11462-11467 (2001)
21. Tamayo, P., Slonim, D., Mesirov, J., Zhu, Q., Kitareewan, S., Dmitrovsky, E., Lander, E.S., Golub, T.: Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. PNAS 96, 2907-2912 (1999)
22. Eisen, M., Spellman, P., Brown, P., Botstein, D.: Cluster Analysis and Display of Genome-wide Expression Patterns. Proceedings of the National Academy of Sciences of the United States of America 95(25), 14863-14868 (1998)