T. Attwood and C. J. Miller, Which craft is best in bioinformatics?, Computers & Chemistry, vol.25, issue.4, pp.329-339, 2001.
DOI : 10.1016/S0097-8485(01)00069-9

A. Zhang, Advanced analysis of gene expression microarray data, ser. Science, Engineering, and Biology Informatics. World Scientific, vol.1, 2006.
DOI : 10.1142/6016

R. Cho, M. Campbell, and E. Winzeler, A Genome-Wide Transcriptional Analysis of the Mitotic Cell Cycle, Molecular Cell, vol.2, issue.1, pp.65-73, 1998.
DOI : 10.1016/S1097-2765(00)80114-8

J. Derisi, L. Iyer, and V. 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

M. Eisen, P. Spellman, P. Brown, and D. Botsein, Cluster analysis and display of genome-wide expression patterns, Proceedings of the National Academy of Sciences of the USA, pp.14-863, 1998.
DOI : 10.1073/pnas.95.25.14863

P. Tamayo and D. Slonim, Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation, Proceedings of the National Academy of Sciences of the USA, pp.2907-2912, 1999.
DOI : 10.1073/pnas.96.6.2907

S. Tavazoie, J. Hughes, M. Campbell, R. Cho, and G. Church, Systematic determination of genetic network architecture, Nature Genetics, vol.22, pp.281-285, 1999.

A. Ben-dor, R. Shamir, and Z. Yakhini, Clustering Gene Expression Patterns, Journal of Computational Biology, vol.6, issue.3-4, pp.281-297, 1999.
DOI : 10.1089/106652799318274

C. Blaschke, L. Hikrschman, and A. Valencia, Co-clustering of biological networks and gene expression data, Bioinformatics, vol.18, pp.145-154, 2002.

]. H. Muller, E. Kenny, and P. Sternberg, Textpresso: An Ontology-Based Information Retrieval and Extraction System for Biological Literature, PLoS Biology, vol.2000, issue.11, pp.145-163, 2004.
DOI : 10.1371/journal.pbio.0020309.t007

G. Churchill, Fundamentals of experimental design for cDNA microarrays, Nature Genetics, vol.32, issue.Supp, pp.490-495, 2002.
DOI : 10.1038/ng1031

S. G. Lee, J. U. Hur, and Y. S. Kim, A graph-theoretic modeling on GO space for biological interpretation of gene clusters, Bioinformatics, vol.20, issue.3, pp.381-386, 2004.
DOI : 10.1093/bioinformatics/btg420

Z. Fang, J. Yang, Y. Li, Q. Luo, and L. Liu, Knowledge guided analysis of microarray data, Journal of Biomedical Informatics, vol.39, issue.4, pp.1-11, 2005.
DOI : 10.1016/j.jbi.2005.08.004

J. Liu, J. Yang, and W. Wang, Biclustering in gene expression data by tendency, Computational Systems Bioinformatics Conference, CSB 2004 Proceedings, pp.182-193, 2004.

D. Hanisch, A. Zien, R. Zimmer, and T. Lengauer, Co-clustering of biological networks and gene expression data, Bioinformatics, vol.18, issue.Suppl 1, pp.145-154, 2002.
DOI : 10.1093/bioinformatics/18.suppl_1.S145

A. Riva, A. Carpentier, B. Torresani, and A. Henaut, Comments on selected fundamental aspects of microarray analysis, Computational Biology and Chemistry, vol.29, issue.5, pp.319-336, 2005.
DOI : 10.1016/j.compbiolchem.2005.08.006
URL : https://hal.archives-ouvertes.fr/hal-01279953

V. Mootha, C. Lindgren, K. Eriksson, and A. Subramanian, PGC-1??-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes, Nature Genetics, vol.34, issue.3, pp.267-273, 2003.
DOI : 10.1038/ng1180

R. Breitling, A. Amtmann, and P. Herzyk, IGA: A simple tool to enhance sensitivity and facilitate interpretation of microarray experiments, BMC Bioinformatics, vol.2005, issue.34, 2004.

S. Kim and D. Volsky, Page: Parametric analysis of gene set enrichment, BMC Bioinformatics, vol.6, issue.1, p.144, 2005.
DOI : 10.1186/1471-2105-6-144

R. Martinez, N. Pasquier, C. Pasquier, M. Collard, and L. Lopez-perez, Co-expressed gene groups analysis (CGGA): An automatic tool for the interpretation of microarray experiments, Journal of Integrative Bioinformatics, vol.3, issue.11, pp.1-12, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00172501

W. Feller, An Introduction to Probability Theory and Its Applications, 1971.

L. Kaufman and P. Rousseeuw, Findings Groups in Data. An introduction to Cluster Analysis, 1990.

J. Banfield and A. Raftery, Model-Based Gaussian and Non-Gaussian Clustering, Biometrics, vol.49, issue.3, pp.803-822, 1993.
DOI : 10.2307/2532201

K. Cios, W. Pedrycz, and R. Swiniarski, Data Mining Methods for Knowledge Discovery, IEEE Transactions on Neural Networks, vol.9, issue.6, 1998.
DOI : 10.1109/TNN.1998.728406

M. Robinson, Funspec : a web based cluster interpreter for yeast, BMC Bioinformatics, vol.3, issue.1, p.35, 2002.
DOI : 10.1186/1471-2105-3-35

S. Draghici and P. Khatri, Global Functional Profiling of Gene Expression Data, Genomics, issue.81, pp.1-7, 2003.
DOI : 10.1007/0-306-47815-3_18

D. 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

D. Hosack and G. Dennis, Identifying biological themes within lists of genes with ease, Genome Biology, vol.4, issue.70, 2003.

C. Pasquier, F. Girardot, K. Jevardat, and R. Christen, THEA: ontology-driven analysis of microarray data, Bioinformatics, vol.20, issue.16, 2004.
DOI : 10.1093/bioinformatics/bth295
URL : https://hal.archives-ouvertes.fr/hal-00170450

P. Pehkonen, G. Wong, and P. Toronen, Theme discovery from gene lists for identification and viewing of multiple functional groups, BMC Bioinformatics, vol.6, issue.1, p.162, 2005.
DOI : 10.1186/1471-2105-6-162

W. Feng, G. Wang, B. Zeeberg, K. Guo, A. Fojo et al., Development of gene ontology tool for biological interpretation of genomic and proteomic data, AMIA Annual Symposium Proceedings, p.839, 2003.

F. Al-shahrour, R. Diaz-uriarte, and J. Dopazo, FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes, Bioinformatics, vol.20, issue.4, pp.578-580, 2004.
DOI : 10.1093/bioinformatics/btg455

T. Beissbarth and T. Speed, GOstat: find statistically overrepresented Gene Ontologies within a group of genes, Bioinformatics, vol.20, issue.9, pp.1464-1465, 2004.
DOI : 10.1093/bioinformatics/bth088

D. Martin, C. Brun, E. Remy, P. Mouren, D. Thieffry et al., Gotoolbox: functional analysis of gene datasets based on gene ontology, Genome Biology, vol.5, issue.12, 2004.
URL : https://hal.archives-ouvertes.fr/inserm-00095249

M. Masseroli, D. Martucci, and F. Pinciroli, GFINDer: Genome Function INtegrated Discoverer through dynamic annotation, statistical analysis, and mining, Nucleic Acids Research, vol.32, issue.Web Server, pp.293-300, 2004.
DOI : 10.1093/nar/gkh432
URL : http://doi.org/10.1093/nar/gkh432

N. Shah and N. Fedoroff, CLENCH: a program for calculating Cluster ENriCHment using the Gene Ontology, Bioinformatics, vol.20, issue.7, pp.1196-1197, 2004.
DOI : 10.1093/bioinformatics/bth056

S. Maere, K. Heymans, and M. Kuiper, BiNGO: a Cytoscape plugin to assess overrepresentation of Gene Ontology categories in Biological Networks, Bioinformatics, vol.21, issue.16, pp.3448-3449, 2005.
DOI : 10.1093/bioinformatics/bti551

R. Fisher, On the Interpretation of ?? 2 from Contingency Tables, and the Calculation of P, Journal of the Royal Statistical Society, vol.85, issue.1, pp.87-94, 1922.
DOI : 10.2307/2340521

K. Kerr and G. Churchill, Statistical design and the analyissi of gene expression microarray data, Genetics Research, vol.77, pp.123-128, 2001.

M. Man, Z. Wang, and Y. Wang, POWER_SAGE: comparing statistical tests for SAGE experiments, Bioinformatics, vol.16, issue.11, pp.953-959, 2000.
DOI : 10.1093/bioinformatics/16.11.953

L. Fisher and G. Van-belle, Biostatistics: A Methodology for the Health Sciences., Biometrics, vol.53, issue.3, 1993.
DOI : 10.2307/2533583

T. Cover and J. Thomas, Elements of information theory, 1991.

C. Blaschke, R. Hoffmann, A. Valencia, and J. Oliveros, Extracting Information Automatically from Biological Literature, Comparative and Functional Genomics, vol.28, issue.5, pp.310-313, 2001.
DOI : 10.1002/cfg.102

L. Tanabe, U. Scherf, L. Smith, L. Lee, J. Hunter et al., Medminer: an internet text-mining tool for biomedical information, with application to gene expression profiling, Biotechniques, vol.27, issue.6, pp.1210-1217, 1999.

C. Perez-iratxeta, P. Bork, and M. Andrade, Exploring medline abstracts with xplormed, Drugs of Today, vol.38, issue.6, pp.381-389, 2002.
DOI : 10.1358/dot.2002.38.6.678344

T. Rindflesch, L. Tanabe, J. Weinstein, and L. Hunter, EDGAR: Extraction of Drugs, Genes And Relations from the Biomedical Literature, Biocomputing 2000, pp.517-528, 2000.
DOI : 10.1142/9789814447331_0049

J. Chiang, H. Yu, and H. Hsu, GIS: a biomedical text-mining system for gene information discovery, Bioinformatics, vol.20, issue.1, pp.120-121, 2004.
DOI : 10.1093/bioinformatics/btg369

D. Masys, Use of keyword hierarchies to interpret gene expression patterns, Bioinformatics, vol.17, issue.4, pp.319-326, 2001.
DOI : 10.1093/bioinformatics/17.4.319

K. Zhang and H. Zhao, Assessing reliability of gene clusters from gene expression data, Functional & Integrative Genomics, vol.1, issue.3, pp.156-173, 2000.
DOI : 10.1007/s101420000019

M. Halkidi, Y. Batistakis, and M. Vazirgiannis, On clustering validation techniques, Journal of Intelligent Information Systems, vol.17, issue.2/3, pp.107-145, 2001.
DOI : 10.1023/A:1012801612483

F. Azuaje, A cluster validity framework for genome expression data, Bioinformatics, vol.18, issue.2, pp.319-320, 2002.
DOI : 10.1093/bioinformatics/18.2.319

A. Ben-hur, A. Elisseeff, and I. Guyon, A stability based method for discovering structure in clustered data, Biocomputing 2002, pp.6-17, 2002.
DOI : 10.1142/9789812799623_0002

S. Datta and S. Datta, Comparisons and validation of statistical clustering techniques for microarray gene expression data, Bioinformatics, vol.19, issue.4, pp.459-466, 2003.
DOI : 10.1093/bioinformatics/btg025

C. Giurcaneanu, I. Tabus, I. Shmulevich, and W. Zhang, Stability-based cluster analysis applied to microarray data, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings., pp.57-60, 2003.
DOI : 10.1109/ISSPA.2003.1224814

M. Smolkin and D. Ghosh, Cluster stability scores for microarray data in cancer studies, BMC Bioinformatics, vol.4, issue.36, 2003.

D. Elihu, P. Nechama, and L. Menachem, Mercury exposure and effects at a thermometer factory, Scandinavian Journal of Work Environmental Health, vol.8, issue.1, pp.161-166, 2004.

P. Rousseeuw, Silhouettes: A graphical aid to the interpretation and validation of cluster analysis, Journal of Computational and Applied Mathematics, vol.20, pp.53-65, 1987.
DOI : 10.1016/0377-0427(87)90125-7

J. Liu, J. Yang, and W. Wang, Gene ontology friendly biclustering of expression profiles, Computational Systems Bioinformatics Conference, CSB 2004 Proceedings, pp.436-447, 2004.