Binary matrix factorization for analyzing gene expression data

Data Mining and Knowledge Discovery

Volumn 20, Issue 1, 2010, Pages 28-52

  Zhang, Zhong Yuan ^a   Li, Tao ^b   Ding, Chris ^c   Ren, Xian Wen ^d   Zhang, Xiang Sun ^d  

^a CENTRAL UNIVERSITY OF FINANCE AND ECONOMICS   (China)

^b FLORIDA INTERNATIONAL UNIVERSITY   (United States)

^c The University of Texas at Arlington   (United States)

^d CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

Biclustering; Binary matrix; Boundedness property of NMF; Non negative matrix factorization

Indexed keywords

BICLUSTERING; BINARY MATRIX; BOUNDEDNESS PROPERTIES; CLINICAL DIAGNOSIS; EXPRESSION DATA; GENE EXPRESSION DATA; GLOBALOPTIMUM; GREEDY STRATEGIES; MICROARRAY DATA; MICROARRAY TECHNOLOGIES; NONNEGATIVE MATRIX FACTORIZATION; REAL DATA SETS; SINGLE CHIPS; TRADITIONAL CLUSTERING;

BIOCHEMISTRY; BLIND SOURCE SEPARATION; CLUSTER ANALYSIS; DATA MINING; DIAGNOSIS; FACTORIZATION; GENE EXPRESSION; LIGHT MEASUREMENT; MATRIX ALGEBRA; MOLECULAR BIOLOGY;

CLUSTERING ALGORITHMS;

EID: 76749101527     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-009-0145-2     Document Type: Article

References (47)

1. Ben-Dor A, Chor B, Karp R, Yakhini Z (2002) Discovering local structure in gene expression data: the order-preserving submatrix problem. In: RECOMB '02: proceedings of the 6th annual international conference on computational biology. ACM, New York, pp 49-57
2. M Berry M Browne A Langville P Pauca R Plemmons 2007 Algorithms and applications for approximate nonnegative matrix factorization Comput Stat Data Anal 52 1 155 173 05560147 10.1016/j.csda.2006.11.006 2409971 (Pubitemid 47331703)
3. J-P Brunet P Tamayo TR Golub JP Mesirov 2004 Metagenes and molecular pattern discovery using matrix factorization Proc Natl Acad Sci USA 101 12 4164 4169 10.1073/pnas.0308531101 (Pubitemid 38405900)
4. P Carmona-Saez RD Pascual-Marqui F Tirado JM Carazo A Pascual-Montano 2006 Biclustering of gene expression data by non-smooth non-negative matrix factorization BMC Bioinformatics 7 1 78 10.1186/1471-2105-7-78
5. M Chee R Yang E Hubbell A Berno X Huang D Stern J Winkler D Lockhart M Morris S Fodor 1996 Accessing genetic information with high density DNA arrays Science 274 610 614 10.1126/science.274.5287.610 (Pubitemid 26360440)
6. Cheng Y, Church G (2000) Biclustering of expression data. In: Proceedings of the 8th international conference on intelligent systems for molecular biology, pp 93-103
7. Cooper M, Foote J (2002) Summarizing video using non-negative similarity matrix factorization. In: Proceedings of IEEE workshop on multimedia signal processing, pp 25-28
8. Dhillon I, Sra S (2005) Generalized nonnegative matrix approximations with Bregman divergences. In: Advances in neural information processing systems, vol 17. MIT Press, Cambridge
9. Ding C, He X, Simon H (2005) On the equivalence of nonnegative matrix factorization and spectral clustering. In: Proceedings of SIAM data mining conference
10. Ding C, Li T, Jordan M (2006) Convex and semi-nonnegative matrix factorizations for clustering and low-dimension representation. Technical Report LBNL-60428, Lawrence Berkeley National Laboratory, University of California, Berkeley
11. Ding C, Li T, Peng W (2006) Nonnegative matrix factorization and probabilistic latent semantic indexing: equivalence, chi-square statistic, and a hybrid method. In: Proceedings of national conference on artificial intelligence (AAAI-06)
12. S Draghici P Khatri P Bhavsar A Shah SA Krawetz MA Tainsky 2003 Onto-tools, the toolkit of the modern biologist: onto-express, onto-compare, onto-design and onto-translate Nucleic Acids Res 31 13 3775 3781 10.1093/nar/gkg624 (Pubitemid 37442244)
13. MB Eisen PT Spellman PO Brown D Botstein 1998 Cluster analysis and display of genome-wide expression patterns Proc Natl Acad Sci 95 14863 14868 10.1073/pnas.95.25.14863 (Pubitemid 29003722)
14. S Fodor J Read M Pirrung L Stryer A Lu D Solas 1991 Light-directed, spatially addressable parallel chemical synthesis Science 251 767 783 10.1126/science.1990438
15. Gaussier E, Goutte C (2005) Relation between plsa and nmf and implications. In: SIGIR '05, pp 601-602
16. GJ Gordon RV Jensen L-L Hsiao SR Gullans JE Blumenstock S Ramaswamy WG Richards DJ Sugarbaker R Bueno 2002 Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesothelioma Cancer Res 62 4963 4967
17. PO Hoyer 2004 Non-negative matrix factorization with sparseness constraints J Mach Learn Res 5 1457 1469 2248024
18. W Huber, et al. 2002 Variance stabilization applied to microarray data calibration and to the quantification of differential expression Bioinformatics 18 Suppl 1 S96 S104
19. T Ideker, et al. 2000 Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data J Comput Biol 7 6 805 817 10.1089/10665270050514945
20. J Ihmels G Friedlander S Bergmann O Sarig Y Ziv N Barkai 2002 Revealing modular organization in the yeast transcriptional network Nature Genet 31 370 377
21. J Ihmels S Bergmann N Barkai 2004 Defining transcription modules using large-scale gene expression data Bioinformatics 20 13 1993 2003 10.1093/bioinformatics/bth166 (Pubitemid 39236551)
22. P Khatri S Draghici G Ostermeier S Krawetz 2002 Profiling gene expression using onto-express Genomics 79 2 266 270 10.1006/geno.2002.6698
23. H Kim H Park 2007 Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis Bioinformatics 23 12 1495 1502 10.1093/bioinformatics/btm134 (Pubitemid 47244474)
24. M Koyuturk A Grama N Ramakrishnan 2006 Non-orthogonal decomposition of binary matrices for bounded-error data compression and analysis ACM Trans Math Softw 32 1 33 69 10.1145/1132973.1132976 2272351 (Pubitemid 43924956)
25. la Torre FD, Kanade T (2006) Discriminative cluster analysis. In: Proceedings of the 23rd international conference on machine learning (ICML 2006)
26. D Lee HS Seung 1999 Learning the parts of objects by non-negative matrix factorization Nature 401 788 791 10.1038/44565 (Pubitemid 29512513)
27. Lee D, Seung HS (2001) Algorithms for non-negative matrix factorization. In: Dietterich TG, Tresp V (eds) Advances in neural information processing systems, vol 13. MIT Press, Cambridge
28. Li T (2005) A general model for clustering binary data. In: Proceedings of the 11th ACM SIGKDD international conference, pp 188-197
29. Li S, Hou X, Zhang H, Cheng Q (2001) Learning spatially localized, parts-based representation. In: Proceedings of IEEE conference on computer vision and pattern recognition, pp 207-212
30. T Li C Zhang M Ogihara 2004 A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression Bioinformatics 20 15 2429 2437 10.1093/bioinformatics/bth267 (Pubitemid 39429915)
31. SC Madeira, et al. 2004 Biclustering algorithms for biological data analysis: a survey IEEE Trans Comput Biol Bioinformatics 1 24 45 10.1109/TCBB.2004.2
32. P Paatero U Tapper 1994 Positive matrix factorization: a non-negative factor model with optimal utilization of error estimates of data values Environmetrics 5 111 126 10.1002/env.3170050203
33. Pauca VP, Shahnaz F, Berry M, Plemmons R (2004) Text mining using non-negative matrix factorization. In: Proceedings of SIAM international conference on data mining, pp 452-456
34. A Prelic S Bleuler P Zimmermann A Wille P Buhlmann W Gruissem L Hennig L Thiele E Zitzler 2006 A systematic comparison and evaluation of biclustering methods for gene expression data Bioinformatics 22 9 1122 1129 10.1093/bioinformatics/btl060
35. D Rocke B Durbin 2001 A model for measurement error for gene expression arrays J Comput Biol 8 6 557 569 10.1089/106652701753307485 (Pubitemid 34053496)
36. Sha F, Saul L, Lee D (2003) Multiplicative updates for nonnegative quadratic programming in support vector machines. In: Advances in neural information processing systems, vol 15, pp 1041-1048
37. R Sharan A Maron-Katz R Shamir 2003 Click and expander: a system for clustering and visualizing gene expression data Bioinformatics 19 14 1787 1799 10.1093/bioinformatics/btg232 (Pubitemid 37220471)
38. Srebro N, Rennie J, Jaakkola T (2005) Maximum margin matrix factorization. In: Advances in neural information processing systems. MIT Press, Cambridge
39. A Strehl J Ghosh 2003 Cluster ensembles-a knowledge reuse framework for combining multiple partitions J Mach Learn Res 3 583 617 1084.68759 10.1162/153244303321897735 1991087
40. Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, Lander E, Golub T (1999) Interpreting patterns of gene expression with self-organizing maps. In: Proceedings of the national academy of sciences of USA, vol 96
41. A Tanay R Sharan R Shamir 2002 Discovering statistically significant biclusters in gene expression data Bioinformatics 18 90001 S136 S144
42. A Tanay R Sharan M Kupiec R Shamir RM Karp 2004 Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genome-wide data Proc Natl Acad Sci USA 101 9 2981 2986 10.1073/pnas.0308661100 (Pubitemid 38327722)
43. Vavasis SA (2007) On the complexity of nonnegative matrix factorization. http://arxiv.org/abs/0708.4149
44. Y-L Xie P Hopke P Paatero 1999 Positive matrix factorization applied to a curve resolution problem J Chemom 12 6 357 364 10.1002/(SICI)1099-128X(199811/ 12)12:6<357::AID-CEM523>3.0.CO;2-S
45. Xu W, Liu X, Gong Y (2003) Document clustering based on non-negative matrix factorization. In: Proceedings of ACM conference on research and development in IR(SIGIR), Toronto, pp 267-273
46. Zeimpekis D, Gallopoulos E (2005) Clsi: a flexible approximation scheme from clustered term-document matrices. Proceedings of SIAM data mining conference, pp 631-635
47. Zhang Z, Li T, Ding C, Zhang X (2007) Binary matrix factorization and applications. In: Proceedings of 2007 IEEE international conference on data mining