Finding biclusters by random projections

Theoretical Computer Science

Volumn 368, Issue 3, 2006, Pages 217-230

  Lonardi, Stefano ^a   Szpankowski, Wojciech ^b   Yang, Qiaofeng ^a  

^a University of California Riverside   (United States)

^b Purdue University   (United States)

Author keywords

Bicliques; Biclustering; Co clustering; Textual matrices; Two way clustering

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; PROBLEM SOLVING; STATISTICAL METHODS;

BICLIQUES; BICLUSTERING; CO-CLUSTERING; TEXTUAL MATRICES; TWO-WAY CLUSTERING;

COMPUTATIONAL COMPLEXITY;

EID: 33751001062     PISSN: 03043975     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.tcs.2006.09.023     Document Type: Article

References (32)

1. C.C. Aggarwal, C. Procopiuc, J.L. Wolf, P.S. Yu, J.S. Park, Fast algorithms for projected clustering, in: Proc. ACM SIGMOD Internat. Conf. on Management of Data (SIGMOD-99), SIGMOD Record, Vol. 28(2), ACM Press, New York, 1999, pp. 61-72.
2. R. Agrawal, J. Gehrke, D. Gunopulos, P. Raghavan, Automatic subspace clustering of high dimensional data for data mining applications, in: Proc. ACM SIGMOD Internat. Conf. on Management of Data (SIGMOD-98), ACM SIGMOD Record, Vol. 27(2), ACM Press, New York, 1998, pp. 94-105.
3. Ben-Dor A., Chor B., Karp R., and Yakhini Z. Discovering local structure in gene expression data: the order-preserving submatrix problem. Proc. Sixth Internat. Conf. on Computational Molecular Biology (RECOMB 2002) (2002), ACM Press, New York 45-55
4. Cheng Y., and Church G.M. Biclustering of expression data. Proc. Eighth Internat. Conf. on Intelligent Systems for Molecular (ISMB-00) (2000), AAAI Press, Menlo Park, CA 93-103
5. Dawande M., Keskinocak P., Swaminathan J.M., and Tayur S. On bipartite and multipartite clique problems. J. Algorithms 41 (2001) 388-403
6. Dhillon I. Co-clustering documents and words using bipartite spectral graph partitioning. Proc. Seventh ACM SIGKDD Internat. Conf. on Knowledge Discovery and Data Mining (KDD-01) (2001), ACM Press, New York 269-274
7. Dhillon I., Mallela S., and Modha D. Information-theoretic co-clustering. Proc. Seventh ACM SIGKDD Internat. Conf. on Knowledge Discovery and Data Mining (KDD-03) (2001), ACM Press, New York 89-98
8. Garey M.R., and Johnson D.S. Computers and Intractability: A Guide to the Theory of NP-Completeness (1979), Freeman, New York, NY
9. M. Grigni, F. Manne, On the complexity of the generalized block distribution, in: Proc. of Irregular'96, The Third Internat. Workshop on Parallel Algorithms for Irregularly Structured Problems, Lecture Notes in Computer Science, Vol. 1117, Springer, Berlin, 1996, pp. 319-326.
10. M. Gu, H. Zha, C. Ding, X. He, H. Simon, Spectral relaxation models and structure analysis for k-way graph clustering and bi-clustering, Technical Report CSE-01-007, Department of Computer Science and Engineering, Pennsylvania State University, 2001.
11. Hanisch D., Zien A., Zimmer R., and Lengauer T. Co-clustering of biological networks and gene expression data. Proc. Eighth Internat. Conf. on Intelligent Systems for Molecular (ISMB-02) (2002), AAAI Press, Menlo Park, CA 145-154
12. Hartigan J.A. Direct clustering of a data matrix. J. Amer. Statist. Assoc. 67 337 (1972) 123-129
13. Hastie T., Tibshirani R., Eisen M., Alizadeh A., Levy R., Staudt L., Chan W., Botstein D., and Brown P. 'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns. Genome Biol. 1 2 (2000) 1-21
14. Hochbaum D.S. Approximating clique and biclique problems. J. Algorithms 29 1 (1998) 174-200
15. Kluger Y., Basri R., Chang J., and Gerstein M. Spectral biclustering of microarray data: coclustering genes and conditions. Genome Res. 13 4 (2003) 703-716
16. Koyuturk M., Szpankowski W., and Grama A. Biclustering gene-feature matrices for statistically significant dense patterns. IEEE Computer Society Bioinformatics Conf. Stanford, CA (2004) 480-483
17. Kumar R., Raghavan P., Rajagopalan S., and Tomkins A. Trawling the web for emerging cyber-communities. Comput. Networks 31 11-16 (1999) 1481-1493
18. Lazzeroni L., and Owen A. Plaid models for gene expression data. Statist. Sinica 12 1 (2002) 61-86
19. Liu J., Yang J., and Wang W. Biclustering in gene expression data by tendency. IEEE Computational Systems Bioinformatics Conf. (CSB'04) (2004) 224-235
20. Melkman A.A., and Shaham E. Sleeved coclustering. Proc. 2004 ACM SIGKDD Internat. Conf. on Knowledge Discovery and Data Mining. Seattle, WA (2004) 635-640
21. Mishra N., Ron D., and Swaminathan R. On finding large conjunctive clusters. Proc. ACM Conf. on Computational Learning Theory (COLT'03) (2003) 448-462
22. T.M. Murali, S. Kasif, Extracting conserved gene expression motifs from gene expression data, in: Proc. Pacific Symp. on Biocomputing (PSB'03), 2003, pp. 77-88.
23. D.V. Pasechnik, Bipartite sandwiches, Technical Report, available at 〈http://arXiv.org/abs/math.CO/9907109〉, 1999.
24. R. Peeters, The maximum-edge biclique problem is NP-complete, Technical Report 789, Faculty of Economics and Business Administration, Tilberg University, 2000.
25. Procopiuc M., Jones M., Agarwal P., and Murali T.M. A Monte Carlo algorithm for fast projective clustering. Proc. 2002 Internat. Conf. on Management of Data (SIGMOD'02) (2002) 418-427
26. Reinert G., Schbath S., and Waterman M.S. Probabilistic and statistical properties of words: an overview. J. Comput. Biol. 7 (2000) 1-46
27. Sheng Q., Moreau Y., and Moor B.D. Biclustering microarray data by Gibbs sampling. Proc. of European Conf. on Computational Biology (ECCB'03) (2003) 196-205
28. Szpankowski W. Average Case Analysis of Algorithms on Sequences (2001), Wiley Interscience, New York
29. A. Tanay, R. Sharan, R. Shamir, Discovering statistically significant biclusters in gene expression data, in: Proc. 10th Internat. Conf. on Intelligent Systems for Molecular Biology (ISMB'02), Bioinformatics, Vol. 18, 2002, pp. S136-S144.
30. Wang H., Wang W., Yang J., and Yu P.S. Clustering by pattern similarity in large data sets. Proc. 2002 ACM SIGMOD Internat. Conf. on Management of Data (SIGMOD-02) (2002), ACM Press, New York 394-405
31. J. Yang, H. Wang, W. Wang, P.S. Yu, Enhanced biclustering on gene expression data, in: IEEE Symp. on Bioinformatics and Bioengineering (BIBE'03), 2003, pp. 321-327.
32. Zhang L., and Zhu S. A new clustering method for microarray data analysis. Proc. First IEEE Computer Society Bioinformatics Conf. (CSB'02) (2002), IEEE Press, New York 268-275