R. 1. Ryan, D. P. , and J. M. Matthews, Protein???protein interactions in human disease, Current Opinion in Structural Biology, vol.15, issue.4, pp.441-447, 2005.
DOI : 10.1016/j.sbi.2005.06.001

T. Ito, A comprehensive two-hybrid analysis to explore the yeast protein interactome Proceedings of the National Academy of Science, pp.4569-4574, 2001.

O. Puig, The Tandem Affinity Purification (TAP) Method: A General Procedure of Protein Complex Purification, Methods, vol.24, issue.3, pp.218-247, 2001.
DOI : 10.1006/meth.2001.1183

D. Stoll, Protein microarrays: applications and future challenges, Curr Opin Drug Discov Devel, vol.8, issue.2, pp.239-52, 2005.

W. G. Willats, Phage display: practicalities and prospects, Plant Molecular Biology, vol.50, issue.6, pp.837-54, 2002.
DOI : 10.1023/A:1021215516430

E. Sprinzak, S. Sattath, and H. Margalit, How Reliable are Experimental Protein???Protein Interaction Data?, Journal of Molecular Biology, vol.327, issue.5, pp.919-923, 2003.
DOI : 10.1016/S0022-2836(03)00239-0

G. D. Bader and C. W. , Hogue: An automated method for finding molecular complexes in large protein interaction networks, BMC Bioinformatics, vol.4, issue.2, 2003.

M. Koyuturk, W. Szpankowski, and A. Grama, Assessing Significance of Connectivity and Conservation in Protein Interaction Networks, Journal of Computational Biology, vol.14, issue.6, pp.747-64, 2007.
DOI : 10.1089/cmb.2007.R014

E. Hartuv and R. Shamir, A clustering algorithm based on graph connectivity Information Processing Letters, pp.175-181, 2000.
DOI : 10.1016/s0020-0190(00)00142-3

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.17.1450

S. Brohee and J. Van-helden, Evaluation of clustering algorithms for protein-protein interaction networks, BMC Bioinformatics, vol.7, issue.1, p.488, 2006.
DOI : 10.1186/1471-2105-7-488

X. Li, Computational approaches for detecting protein complexes from protein interaction networks: a survey Ouzounis: An efficient algorithm for large-scale detection of protein families, and I. Jurisica: Protein complex prediction via costbased clustering, Kritikos, G., et al.: Spectral Clustering of Weighted Protein Interaction Networks, pp.3-1575, 2002.

M. B. Eisen, Cluster analysis and display of genome-wide expression patterns, Proceedings of the National Academy of Sciences, vol.24, issue.2, pp.95-14863, 1998.
DOI : 10.1016/0092-8674(81)90326-3

W. K. The-gene-ontology-huh, The Gene Ontology (GO) project in 2006, M.I. Jordan, and Y. Weiss: On Spectral Clustering: Analysis and an algorithm Advances in Neural Information Processing Systems, pp.322-328, 2001.
DOI : 10.1093/nar/gkj021

C. M. Bishop and C. N. Moschopoulos, An enchanced Markov clustering method for detecting protein complexes, 8th IEEE International Conference on BioInformatics and BioEngineering, 2006.

D. Goldberg, S. Bandyopadhyay, and S. K. , Genetic Algorithms in Search, Optimization and Machine Learning Pal: Classification and Learning Using Genetic Algorithms: Applications in Bioinformatics and Web Intelligence: An Introduction to Genetic Algorithms, GALIB, vol.23, issue.24, 1989.

Z. Michalewicz and I. Xenarios, Genetic Algorithms + Data Structures = Evolution Programs DIP: the database of interacting proteins, Nucleic Acids Res, vol.27, issue.281, pp.289-91, 1999.

N. J. Krogan, Global landscape of protein complexes in the yeast Saccharomyces cerevisiae, Nature, vol.57, issue.7084, pp.637-680, 2006.
DOI : 10.1016/0092-8674(85)90117-5

A. C. Gavin, Functional organization of the yeast proteome by systematic analysis of protein complexes, Nature, vol.415, issue.6868, pp.415-141, 2002.
DOI : 10.1038/415141a

A. C. Gavin, Proteome survey reveals modularity of the yeast cell machinery, Nature, vol.134, issue.7084, pp.631-637, 2006.
DOI : 10.1534/genetics.104.040063