M. Ashburner, C. Ball, J. Blake, D. Botstein, H. Butler et al., Gene Ontology: tool for the unification of biology, Nature Genetics, vol.9, issue.1, pp.25-29, 2000.
DOI : 10.1038/75556

P. Lord, R. Stevens, A. Brass, and C. Goble, Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation, Bioinformatics, vol.19, issue.10, pp.1275-1283, 1275.
DOI : 10.1093/bioinformatics/btg153

T. Consortium, The Gene Ontology in 2010: extensions and refinements, Nucl. Acids Res, vol.2010, issue.38, pp.331-335

D. Barrell, E. Dimmer, R. Huntley, D. Binns, O. Donovan et al., The GOA database in 2009--an integrated Gene Ontology Annotation resource, Nucleic Acids Research, vol.37, issue.Database, pp.37-396, 2009.
DOI : 10.1093/nar/gkn803

P. Khatri and S. Draghici, Ontological analysis of gene expression data: current tools, limitations, and open problems, Bioinformatics, vol.21, issue.18, pp.3587-3595, 2005.
DOI : 10.1093/bioinformatics/bti565

D. Huang, B. Sherman, Q. Tan, J. Collins, W. Alvord et al., The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists, Genome Biology, vol.8, issue.9, 2007.
DOI : 10.1186/gb-2007-8-9-r183

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

N. Speer, C. Spieth, and A. Zell, A memetic co-clustering algorithm for gene expression profiles and biological annotation, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753), 2004.
DOI : 10.1109/CEC.2004.1331091

C. Pesquita, D. Faria, A. Falcão, P. Lord, and F. Couto, Semantic Similarity in Biomedical Ontologies, PLoS Computational Biology, vol.6, issue.7, 2009.
DOI : 10.1371/journal.pcbi.1000443.t006

M. Rogers and A. Ben-hur, The use of gene ontology evidence codes in preventing classifier assessment bias, Bioinformatics, vol.25, issue.9, pp.1173-1177, 1173.
DOI : 10.1093/bioinformatics/btp122

Z. Du, L. Li, C. Chen, P. Yu, and J. Wang, G-SESAME: web tools for GO-term-based gene similarity analysis and knowledge discovery, Nucleic Acids Research, vol.37, issue.Web Server, 2009.
DOI : 10.1093/nar/gkp463

M. Popescu, J. Keller, and J. Mitchell, Fuzzy Measures on the Gene Ontology for Gene Product Similarity, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.3, issue.3, pp.263-274, 2006.
DOI : 10.1109/TCBB.2006.37

P. Ganesan, H. Garcia-molina, and J. Widom, Exploiting hierarchical domain structure to compute similarity, ACM Transactions on Information Systems, vol.21, issue.1, pp.64-93, 2003.
DOI : 10.1145/635484.635487
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.456.1964

E. Blanchard, M. Harzallah, and P. Kuntz, A generic framework for comparing semantic similarities on a subsumption hierarchy, 18th European Conference on Artificial Intelligence (ECAI, pp.20-24, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00421382

W. Lee, N. Shah, K. Sundlass, and M. Musen, Comparison of Ontology-based Semantic-Similarity Measures, AMIA Annu Symp Proceedings, pp.384-388, 2008.

P. Resnik, Using Information Content to Evaluate Semantic Similarity in a Taxonomy, IJCAI, pp.448-453, 1995.

J. Jiang and D. Conrath, Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy, International Conference Research on Computational Linguistics (ROCLING X) 1997:9008+

G. Miller, WordNet: a lexical database for English, Communications of the ACM, vol.38, issue.11, pp.39-41, 1995.
DOI : 10.1145/219717.219748

Z. Wu and M. Palmer, Verbs semantics and lexical selection, Proceedings of the 32nd annual meeting on Association for Computational Linguistics -, pp.133-138, 1994.
DOI : 10.3115/981732.981751

D. Lin, An Information-Theoretic Definition of Similarity, ICML '98: Proceedings of the Fifteenth International Conference on Machine Learning, pp.296-304, 1998.

J. Sevilla, V. Segura, A. Podhorski, E. Guruceaga, J. Mato et al., Correlation between Gene Expression and GO Semantic Similarity, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.2, issue.4, pp.330-338, 2005.
DOI : 10.1109/TCBB.2005.50

M. Brameier and C. Wiuf, Co-Clustering and visualization of gene expression data and gene ontology terms for Saccharomyces cervisiae using self organizing maps, Biological Informatics, issue.40, pp.160-173, 2007.

R. Rada, H. Mili, E. Bicknell, and M. Blettner, Development and application of a metric on semantic nets. Systems, Man and Cybernetics, IEEE Transactions, vol.19, pp.17-30, 1989.

A. Nagar and H. Mubaid, A New Path Length Measure Based on GO for Gene Similarity with Evaluation using SGD Pathways, 2008 21st IEEE International Symposium on Computer-Based Medical Systems, pp.590-595, 2008.
DOI : 10.1109/CBMS.2008.27

L. Floridi, Outiline of a Theory of Strongly Semantic Information. Minds Mach, 2004.

A. Schlicker, F. Domingues, J. Rahnenfuhrer, and T. Lengauer, A new measure for functional similarity of gene products based on Gene Ontology, BMC Bioinformatics, vol.77302, pp.3021471-2105, 2006.

J. Wang, Z. Du, R. Payattakool, P. Yu, and C. Chen, A new method to measure the semantic similarity of GO terms, Bioinformatics, vol.23, issue.10, pp.1274-1281, 1274.
DOI : 10.1093/bioinformatics/btm087

R. Othman, S. Deris, and R. Illias, A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences, Journal of Biomedical Informatics, vol.41, issue.1, pp.65-81, 2008.
DOI : 10.1016/j.jbi.2007.05.010

A. Nagar and H. Mubaid, Using path length measure for gene clustering based on similarity of annotation terms, 2008 IEEE Symposium on Computers and Communications, pp.637-642, 2008.
DOI : 10.1109/ISCC.2008.4625765

D. Martin, C. Brun, R. E. Mouren, P. Thieffry, D. Jacq et al., GOToolBox: functional analysis of gene datasets based on Gene Ontology, Genome Biology, vol.512, issue.125, 2004.
URL : https://hal.archives-ouvertes.fr/inserm-00095249

M. Mistry and P. Pavlidis, Gene Ontology term overlap as a measure of gene functional similarity, BMC Bioinformatics, vol.9, issue.1, p.327, 2008.
DOI : 10.1186/1471-2105-9-327

X. Guo, R. Liu, C. Shriver, H. Hu, and M. Liebman, Assessing semantic similarity measures for the characterization of human regulatory pathways, Bioinformatics, vol.22, issue.8, pp.967-973, 2006.
DOI : 10.1093/bioinformatics/btl042

C. Pesquita, D. Faria, H. Bastos, A. Ferreira, A. Couto et al., Metrics for GO based protein semantic similarity: a systematic evaluation, BMC Bioinformatics, vol.9, issue.Suppl 5, 2008.
DOI : 10.1186/1471-2105-9-S5-S4
URL : http://doi.org/10.1186/1471-2105-9-s5-s4

G. Salton and M. Mcgill, Introduction to Modern Information Retrieval, 1983.

N. Polettini, The Vector Space Model in Information Retrieval-Term Weighting Problem, 2004.

O. Bodenreider, M. Aubry, and A. Burgun, NON-LEXICAL APPROACHES TO IDENTIFYING ASSOCIATIVE RELATIONS IN THE GENE ONTOLOGY, Biocomputing 2005, pp.91-102, 2005.
DOI : 10.1142/9789812702456_0010

P. Glenisson, P. Antal, J. Mathys, Y. Moreau, and B. Moor, EVALUATION OF THE VECTOR SPACE REPRESENTATION IN TEXT-BASED GENE CLUSTERING, Biocomputing 2003, pp.391-402, 2003.
DOI : 10.1142/9789812776303_0037

J. Chabalier, J. Mosser, and A. Burgun, A transversal approach to predict gene product networks from ontology-based similarity, BMC Bioinformatics, vol.8, issue.1, p.235, 2007.
DOI : 10.1186/1471-2105-8-235

C. C. Wright, The kappa statistic in reliability studies: use, interpretation, and sample size requirements, Physical Therapy, vol.85, issue.3, pp.257-268, 2005.

S. Blott, F. Camous, C. Gurrin, G. Jones, and A. Smeaton, On the use of Clustering and the MeSH Controlled Vocabulary to Improve MEDLINE Abstract Search, CORIA 2005, pp.41-56

F. Couto, M. Silva, and P. Coutinho, Measuring semantic similarity between Gene Ontology terms. Data Knowl. Eng, pp.137-152, 2007.

. Catia, D. Pessoa, D. Faria, and F. Couto, CESSM : Collaborative Evaluation of Semantic Similarity Measures, JB2009: Challenges in Bioinformatics, 2009.

S. Benabderrahmane, M. Devignes, S. Tabbone, M. Poch, O. Napoli et al., Analyse de données transcriptomiques: Modélisation floue de profils d'expression différentielle et analyse fonctionnelle, Actes duXXVIIì eme congrès Informatique des Organisations et Systèmes d'information et de décision -INFORSID 2009, pp.413-428, 2009.

S. Carbon, A. Ireland, C. Mungall, S. Shu, B. Marshall et al., the Web Presence Working Group: AmiGO: online access to ontology and annotation data, Bioinformatics, vol.2525288, issue.22, pp.288-289, 2009.

K. Ovaska, M. Laakso, and S. Hautaniemi, Fast Gene Ontology based clustering for microarray experiments, BioData Mining, vol.28, issue.11, 2008.
DOI : 10.1093/nar/28.1.27
URL : http://doi.org/10.1186/1756-0381-1-11

R. Intelligo, Table 4 -Evaluation results obtained with the CESSM evaluation tool