J. Derisi, V. Iyer, and P. Brown, Exploring the Metabolic and Genetic Control of Gene Expression on a Genomic Scale, Science, vol.278, issue.5338, pp.680-686, 1997.
DOI : 10.1126/science.278.5338.680

R. Cho, M. Mindrinos, D. Richards, R. Sapolsky, M. Anderson et al., Genomewide mapping with biallelic markers in Arabidopsis thaliana, Nature Genet, vol.23, pp.203-207, 2003.

J. Borevitz, D. Liang, D. Plouffe, H. Chang, T. Zhu et al., Large-Scale Identification of Single-Feature Polymorphisms in Complex Genomes, Genome Research, vol.13, issue.3, pp.513-523, 2003.
DOI : 10.1101/gr.541303

C. Liu, W. Ma, R. Shi, Y. Ou, B. Zhang et al., Possibility of Using DNA Chip Technology for Diagnosis of Human Papillomavirus, BMB Reports, vol.36, issue.4, pp.349-353, 2003.
DOI : 10.5483/BMBRep.2003.36.4.349

D. Locke, R. Segraves, L. Carbone, N. Archidiacono, D. Albertson et al., Large-Scale Variation Among Human and Great Ape Genomes Determined by Array Comparative Genomic Hybridization, Genome Research, vol.13, issue.3, pp.347-357, 2003.
DOI : 10.1101/gr.1003303

J. Hartigan and M. Wong, Algorithm AS 136: A K-Means Clustering Algorithm, Applied Statistics, vol.28, issue.1, pp.100-108, 1979.
DOI : 10.2307/2346830

T. Kohonen, Self-organized formation of topologically correct feature maps, Biological Cybernetics, vol.13, issue.1, pp.59-69, 1982.
DOI : 10.1007/BF00337288

T. Kohonen, Self-Organizing Maps, 2001.

S. Lee and S. Batzogolou, Application of Independent Component Analysis to microarrays, Genome Biology, vol.4, issue.11, p.76, 2003.
DOI : 10.1186/gb-2003-4-11-r76

M. Eisen, P. Spellman, P. Brown, and D. Botstein, Cluster analysis and display of genome-wide expression patterns, Proceedings of the National Academy of Sciences, vol.24, issue.2, pp.14863-14868, 1998.
DOI : 10.1016/0092-8674(81)90326-3

J. Quackenbush, Computational analysis of microarray data, Nature genetics, vol.418, pp.418-427, 2001.

K. Yeung, D. Haynor, and W. Ruzzo, Validating clustering for gene expression data, Bioinformatics, vol.17, issue.4, pp.309-318, 2001.
DOI : 10.1093/bioinformatics/17.4.309

URL : http://bauhaus.cs.washington.edu/homes/kayee/cluster2.pdf

F. Gibbons and F. Roth, Judging the Quality of Gene Expression-Based Clustering Methods Using Gene Annotation, Genome Research, vol.12, issue.10, pp.1574-1581, 2002.
DOI : 10.1101/gr.397002

J. Schuchhardt, A. Beule, A. Malik, H. Wolski, H. Eickoff et al., Normalization strategies for cDNA microarrays, Nucleic Acids Research, vol.28, issue.10, p.47, 2000.
DOI : 10.1093/nar/28.10.e47

URL : http://doi.org/10.1093/nar/28.10.e47

Y. Tu, G. Stolovitzky, and U. Klein, Quantitative noise analysis for gene expression microarray experiments, Proceedings of the National Academy of Sciences, vol.3, issue.13, pp.14031-14036, 2002.
DOI : 10.1038/nbt1296-1675

O. Troyanskaya, M. Cantor, G. Sherlock, P. Brown, T. Hastie et al., Missing value estimation methods for DNA microarrays, Bioinformatics, vol.17, issue.6, pp.520-525, 2001.
DOI : 10.1093/bioinformatics/17.6.520

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.3288

S. Oba, M. Sato, I. Takemasa, M. Monden, K. Matsubara et al., A Bayesian missing value estimation method for gene expression profile data, Bioinformatics, vol.19, issue.16, pp.2088-2096, 2003.
DOI : 10.1093/bioinformatics/btg287

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.294.8828

X. Zhou, X. Wang, and E. Dougherty, Missing-value estimation using linear and non-linear regression with Bayesian gene selection, Bioinformatics, vol.19, issue.17, pp.2302-2307, 2003.
DOI : 10.1093/bioinformatics/btg323

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.2076

S. Bohen, O. Troyanskaya, O. Alter, R. Warnke, D. Botstein et al., Variation in gene expression patterns in follicular lymphoma and the response to rituximab, Proceedings of the National Academy of Sciences, vol.98, issue.24, pp.1926-1930, 2003.
DOI : 10.1073/pnas.241500798

T. Sorlie, R. Tibshirani, J. Parker, T. Hastie, J. Marron et al., Repeated observation of breast tumor subtypes in independent gene expression data sets, Proceedings of the National Academy of Sciences, vol.360, issue.9338, pp.8418-8423, 2003.
DOI : 10.1016/S0140-6736(02)11087-7

M. Garber, O. Troyanskaya, K. Schluens, S. Petersen, Z. Thaesler et al., Diversity of gene expression in adenocarcinoma of the lung, Proceedings of the National Academy of Sciences, vol.17, issue.6, pp.13784-13789, 2001.
DOI : 10.1093/bioinformatics/17.6.520

A. Alizadeh, M. Eisen, R. Davis, C. Ma, I. Lossos et al., Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling, Nature, vol.303, issue.6769, pp.503-511, 2000.
DOI : 10.1038/35000501

A. Gasch, P. Spellman, C. Kao, O. Eisen, M. Storz et al., Genomic Expression Programs in the Response of Yeast Cells to Environmental Changes, Molecular Biology of the Cell, vol.11, issue.12, pp.4241-4257, 2000.
DOI : 10.1091/mbc.11.12.4241

N. Ogawa, J. Derisi, and P. Brown, New Components of a System for Phosphate Accumulation and Polyphosphate Metabolism in Saccharomyces cerevisiae Revealed by Genomic Expression Analysis, Molecular Biology of the Cell, vol.11, issue.12, pp.4309-4321, 2000.
DOI : 10.1091/mbc.11.12.4309

T. Ferea, D. Botstein, P. Brown, and R. Rosenzweig, Systematic changes in gene expression patterns following adaptive evolution in yeast, Proceedings of the National Academy of Sciences, vol.262, issue.2, pp.9721-9726, 1999.
DOI : 10.1046/j.1432-1327.1999.00345.x

P. Spellman, G. Sherlock, M. Zhang, V. Iyer, K. Anders et al., Comprehensive Identification of Cell Cycle-regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization, Molecular Biology of the Cell, vol.9, issue.12, pp.3273-3297, 1998.
DOI : 10.1091/mbc.9.12.3273

L. Liu, D. Hawkins, S. Ghosh, and S. Young, Robust singular value decomposition analysis of microarray data, Proceedings of the National Academy of Sciences, vol.37, issue.2-3, pp.13167-13172, 2003.
DOI : 10.1016/S0531-5565(01)00195-4

K. Yeung, M. Medvedovic, and R. Bumgarner, Clustering geneexpression data with repeated measurements, Genome Biology, vol.4, issue.5, p.34, 2003.
DOI : 10.1186/gb-2003-4-5-r34

J. Nikkilä, P. Törönen, S. Kaski, J. Venna, E. Castren et al., Analysis and visualization of gene expression data using Self-Organizing Maps, Neural Networks, vol.15, issue.8-9, pp.953-966, 2002.
DOI : 10.1016/S0893-6080(02)00070-9

J. Herrero, A. Valencia, and J. Dopazo, A hierarchical unsupervised growing neural network for clustering gene expression patterns, Bioinformatics, vol.17, issue.2, pp.126-136, 2001.
DOI : 10.1093/bioinformatics/17.2.126

J. Herrero and J. Dopazo, Combining Hierarchical Clustering and Self-Organizing Maps for Exploratory Analysis of Gene Expression Patterns, Journal of Proteome Research, vol.1, issue.5, pp.467-470, 2002.
DOI : 10.1021/pr025521v

A. Hsu, S. Tang, and S. Halgamuge, An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data, Bioinformatics, vol.19, issue.16, pp.2131-2140, 2003.
DOI : 10.1093/bioinformatics/btg296

J. Gollub, C. Ball, G. Binkley, J. Demeter, D. Finkelstein et al., The Stanford Microarray Database: data access and quality assessment tools, Nucleic Acids Research, vol.31, issue.1, pp.94-96, 2003.
DOI : 10.1093/nar/gkg078

R. Ihaka and R. Gentleman, A Language for Data Analysis and Graphics, J Comput Graph Stat, vol.5, pp.299-314, 1996.