Pattern discovery in expression profiling data

Current Protocols in Molecular Biology

Volumn , Issue SUPPL. 85, 2009, Pages

  Katagiri, Fumiaki ^a   Glazebrook, Jane ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

Author keywords

Dimensionality reduction; Hierarchical clustering; K means; Multivariate analysis; Pearson correlation coefficient; Principal component analysis; Self organizing map

Indexed keywords

CLUSTER ANALYSIS; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE IDENTIFICATION; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MULTIVARIATE ANALYSIS; NONLINEAR SYSTEM; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; REVIEW; ALGORITHM; ARTICLE; CORRELATION COEFFICIENT; DATA PROCESSING; MULTIFACTOR DIMENSIONALITY REDUCTION; SELF ORGANIZING MAP;

EID: 59749086689     PISSN: 19343639     EISSN: 19343647     Source Type: Journal    
DOI: 10.1002/0471142727.mb2205s85     Document Type: Review

References (26)

1. Alter, O., Brown, P.O., and Botstein, D. 2000. Singular value decomposition for genome-wide expression data processing and modeling. Proc. Natl. Acad. Sci. U.S.A. 97:10101-10106.
2. Batagelj, V. and Mrvar, A. 1998. Pajek - Program for large network analysis. Connections 21:47-57.
3. Davidson, G.S., Hendrickson, B., Johnson, D.K., Meyers, C.E., and Wylie, B.N. 1998. Knowledge mining with VxInsight: Discovery through interaction. J. Intell. Inf. Syst. 11:259-285.
4. Dembele, D. and Kastner, P. 2003. Fuzzy C-means method for clusteringmicroarray data. Bioinformatics 19:973-980.
5. Eichler, G.S., Huang, S., and Ingber, D.E. 2003. Gene expression dynamics inspector (GEDI): For integrative analysis of expression profiles. Bioinformatics 19:2321-2322.
6. Eisen, M.B., Spellman, P.T., Brown, P.O., and Botstein, D. 1998. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. U.S.A. 95:14863-14868.
7. Gasch, A.P. and Eisen, M.B. 2002. Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering. Genome Biol. 3:RESEARCH0059.
8. Hastie, T., Tibshirani, R., Eisen, M.B., Alizadeh, A., Levy, R., Staudt, L., Chan, W.C., Botstein, D., and Brown, P. 2000. 'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns. Genome Biol. 1:RESEARCH0003.
9. Herwig, R., Poustka, A.J., Muller, C., Bull, C., Lehrach, H., and O'Brien, J. 1999. Largescale clustering of cDNA-fingerprinting data. Genome Res. 9:1093-1105.
10. Hirai, M.Y., Yano, M., Goodenowe, D.B., Kanaya, S., Kimura, T., Awazuhara, M., Arita, M., Fujiwara, T., and Saito, K. 2004. Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana. Proc. Natl. Acad. Sci. U.S.A. 101:10205-10210.
11. Holter, N.S., Mitra, M., Maritan, A., Cieplak, M., Banavar, J.R., and Fedoroff, N.V. 2000. Fundamental patterns underlying gene expression profiles: Simplicity from complexity. Proc. Natl. Acad. Sci. U.S.A. 97:8409-8414.
12. Katagiri, F. and Glazebrook, J. 2003. Local context finder (LCF) reveals multidimensional relationships among mRNA expression profiles of Arabidopsis responding to pathogen infection. Proc. Natl. Acad. Sci. U.S.A. 100:10842-10847.
13. Kaufman, L. and Rousseeuw, P.J. 1990. Finding Groups in Data. John Wiley & Sons, Inc., Hoboken, N.J.
14. Kim, S.K., Lund, J., Kiraly, M., Duke, K., Jiang, M., Stuart, J.M., Eizinger, A., Wylie, B.N., and Davidson, G.S. 2001. A gene expression map for Caenorhabditis elegans. Science 293:2087-2092.
15. Kishino, H. and Waddell, P.J. 2000. Correspondence analysis of genes and tissue types and finding genetic links from microarray data. Genome Inform. Ser.Workshop Genome Inform. 11:83-95.
16. Kohonen, T. 1997. Self-Organizing Maps. Springer, Berlin.
17. Li, H. and Gui, J. 2006. Gradient directed regularization for sparse Gaussian concentration graphs, with applications to inference of genetic networks. Biostatistics 7:302-317.
18. MacQueen, J.B. 1967. Some methods for classification and analysis of multivariate observations. In Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, pp. 281-297. University of California Press, Berkeley, Calif.
19. Roweis, S.T. and Saul, L.K. 2000. Nonlinear dimensionality reduction by locally linear embedding. Science 290:2323-2326.
20. Schafer, J. and Strimmer, K. 2005. An empirical bayes approach to inferring large-scale gene association networks. Bioinformatics 21:754-764.
21. Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B., and Ideker, T. 2003. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 13:2498-2504.
22. Tamayo, P., Slonim, D., Mesirov, J., Zhu, Q., Kitareewan, S., Dmitrovsky, E., Lander, E.S., and Golub, T.R. 1999. Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. Proc. Natl. Acad. Sci. U.S.A. 96:2907-2912.
23. Tavazoie, S., Hughes, J.D., Campbell, M.J., Cho, R.J., and Church, G.M. 1999. Systematic determination of genetic network architecture. Nat. Genet. 22:281-285.
24. Tenenbaum, J.B., de Silva, V., and Langford, J.C. 2000. A global geometric framework for nonlinear dimensionality reduction. Science 290:2319-2323.
25. Teschendorff, A.E., Journee, M., Absil, P.A., Sepulchre, R., and Caldas, C. 2007. Elucidating the altered transcriptional programs in breast cancer using independent component analysis. PLoS Comput. Biol. 3:e161.
26. Van Poecke, R.M., Sato, M., Lenarz-Wyatt, L., Weisberg, S., and Katagiri, F. 2007. Natural variation in RPS2-mediated resistance among Arabidopsis accessions: Correlation between gene expression profiles and phenotypic responses. Plant Cell 19:4046-4060.