J. Moult, K. Fidelis, A. Kryshtafovych, B. Rost, T. Hubbard et al., Critical assessment of methods of protein structure prediction-round vii, Proteins, vol.69, issue.8, pp.3-9, 2007.

C. A. Rohl, C. E. Strauss, K. M. Misura, and D. Baker, Protein structure prediction using Rosetta, Methods Enzymol, vol.383, pp.66-93, 2004.

S. H. Gellman and D. N. Woolfson, Mini-proteins Trp the light fantastic, Nat. Struct. Biol, vol.9, issue.6, pp.408-418, 2002.

J. Maupetit, P. Derreumaux, and P. Tufféry, A fast method for large-scale de novo peptide and miniprotein structure prediction, J. Comput. Chem, vol.31, issue.4, pp.726-764, 2010.

J. Maupetit, P. Derreumaux, and P. Tufféry, PEP-FOLD: an online resource for de novo peptide structure prediction, Nucleic Acids Res, vol.37, pp.498-503, 2009.

A. C. Camproux, R. Gautier, and P. Tufféry, A hidden markov model derived structural alphabet for proteins, J. Mol. Biol, vol.339, issue.3, pp.591-605, 2004.

J. C. Gelly, A. G. De-brevern, and S. Hazout, Protein 'Protein Peeling': an approach for splitting a 3D protein structure into compact fragments, Bioinformatics, vol.22, pp.129-162, 2006.
URL : https://hal.archives-ouvertes.fr/inserm-00133725

J. C. Gelly, C. Etchebest, S. Hazout, and A. G. De-brevern, Protein Peeling 2: a web server to convert protein structures into series of protein units, Nucleic Acids Res, vol.34, pp.75-83, 2006.
URL : https://hal.archives-ouvertes.fr/inserm-00133731

J. C. Gelly and A. G. De-brevern, Protein Peeling 3D: New tools for analyzing protein structures, Bioinformatics, vol.27, pp.132-133, 2011.
URL : https://hal.archives-ouvertes.fr/inserm-00568165

G. Faure, A. Bornot, and A. G. De-brevern, Analysis of protein contacts into Protein Units. Biochimie, vol.91, pp.876-887, 2009.

A. G. Murzin, S. E. Brenner, T. Hubbard, and C. Chothia, SCOP: a structural classification of proteins database for the investigation of sequences and structures, J Mol Biol, vol.247, pp.536-540, 1995.

L. Holm, C. Sander, and C. , Parser for protein folding units, Proteins, vol.19, pp.256-68, 1994.

S. Jones, M. Stewart, A. Michie, M. B. Swindells, C. Orengo et al., Domain assignment for protein structures using a consensus approach: characterization and analysis, Protein Sci, vol.7, pp.233-242, 1998.

F. Pilot, J. M. Philippe, C. Lemmers, J. P. Chauvin, and T. Lecuit, Developmental control of nuclear morphogenesis and anchoring by charleston, identified in a functional genomic screen of Drosophila cellularisation, Development, vol.133, issue.4, pp.711-734, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00088580

M. Defrance, R. Janky, O. Sand, and J. Van-helden, Using RSAT oligo-analysis and dyad-analysis tools to discover regulatory signals in nucleic sequences, Nat. Protoc, vol.3, pp.1589-1603, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01624304

S. Aerts, X. J. Quan, A. Claeys, M. Sanchez, P. Tate et al., Robust target gene discovery through transcriptome perturbations and genome-wide enhancer predictions in Drosophila uncovers a regulatory basis for sensory specification, PLoS Biology, vol.8, issue.7, p.1000435, 2010.

J. R. Bosch, J. A. Benavides, and T. W. Cline, The TAGteam DNA motif controls the timing of Drosophila preblastoderm transcription, Development, vol.133, issue.10, pp.1967-77, 2006.

H. L. Liang, C. Y. Nien, H. Y. Liu, M. M. Metzstein, N. Kirov et al., The zinc-finger protein Zelda is a key activator of the early zygotic genome in Drosophila, Nature, vol.456, issue.7220, pp.400-403, 2008.

M. M. Harrison, M. R. Botchan, and T. W. , Cline and Grainyhead and Zelda compete for binding to the promoters of the earliest-expressed Drosophila genes, Dev. Biol, vol.345, issue.2, pp.248-55, 2010.

S. T. Smith, S. Petruk, Y. Sedkov, E. Cho, S. Tillib et al., Modulation of heat shock gene expression by the TAC1 chromatin-modifying complex, Nat. Cell Biol, vol.6, issue.2, pp.162-169, 2004.

M. Thomas-chollier, M. Defrance, A. Medina-rivera, O. Sand, C. Herrmann et al., RSAT 2011: Regulatory Sequence Analysis Tools
URL : https://hal.archives-ouvertes.fr/hal-01624291

A. Bevilacqua, M. T. Fiorenza, and F. Mangia, A developmentally regulated GAGA box-binding factor and Sp1 are required for transcription of the hsp70.1 gene at the onset of mouse zygotic genome activation, Development, vol.127, issue.7, pp.1541-51, 2000.

S. Pagans, M. Ortiz-lombardía, M. L. Espinás, J. Bernués, and F. Azorín, The Drosophila transcription factor tramtrack (TTK) interacts with Trithorax-like (GAGA) and represses GAGA-mediated activation, Nucleic Acids Res, vol.30, issue.20, pp.4406-4419, 2002.

W. Tadros and H. D. Lipshitz, The maternal-to-zygotic transition: a play in two acts, Development, vol.136, pp.3033-3042, 2009.

F. Ozsolak, S. Kapranov, S. W. Foissac, E. Kim, A. P. Fishilevich et al., Comprehensive polyadenylation site maps in yeast and human reveal pervasive alternative polyadenylation, Cell, vol.143, issue.6, pp.1018-1047, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01215317

C. Mayr and D. P. Bartel, Widespread shortening of 3'UTRs by alternative cleavage and polyadenylation activates oncogenes in cancer cells, Cell, vol.138, issue.4, pp.673-84, 2009.

V. L. Texier, J. J. Riethoven, V. Kumanduri, C. Gopalakrishnan, F. Lopez et al.,

E. B. Brodie-of-brodie, S. Nicolay, M. Touchon, B. Audit, Y. D'aubenton-carafa et al., From DNA sequence analysis to modeling replication in the human genome, Phys Rev Lett, vol.94, p.248103, 2005.
URL : https://hal.archives-ouvertes.fr/ensl-00175517

B. Audit, S. Nicolay, M. Huvet, M. Touchon, Y. D'aubenton-carafa et al., DNA replication timing data corroborate in silico human replication origin predictions, Phys Rev Lett, vol.99, p.248102, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00337618

M. Huvet, S. Nicolay, M. Touchon, B. Audit, Y. D'aubenton-carafa et al., Human gene organization driven by the coordination of replication and transcription, Genome Res, vol.17, pp.1278-1285, 2007.
URL : https://hal.archives-ouvertes.fr/ensl-00198451

C. L. Chen, L. Duquenne, B. Audit, G. Guilbaud, A. Rappailles et al., Replication-associated mutational asymmetry in the human genome, Mol Biol Evol
URL : https://hal.archives-ouvertes.fr/hal-01557088

C. L. Chen, A. Rappailles, L. Duquenne, M. Huvet, G. Guilbaud et al., Impact of replication timing on non-CpG and CpG substitution rates in mammalian genomes, Genome Res, vol.20, pp.447-457, 2010.
URL : https://hal.archives-ouvertes.fr/ensl-00517756

R. S. Hansen, S. Thomas, R. Sandstrom, T. K. Canfield, R. E. Thurman et al., Sequencing newly replicated DNA reveals widespread plasticity in human replication timing, Proc Natl Acad Sci U S A, vol.107, pp.139-144

A. Baker, B. Audit, C. L. Chen, B. Moindrot, A. Leleu et al., Replication domains are self-interacting chromatin structural units, Genome Res

A. Rappailles, G. Guilbaud, A. Baker, C. L. Chen, A. Arneodo et al., Sequential References

A. P. Morris and L. R. Cardon, Handbook of statistical genetics, vol.2, pp.1238-1263, 2007.

L. A. Hindorff, P. Sethupathy, H. A. Junkins, E. M. Ramos, J. P. Mehta et al., Potential etiologic and functional implications of genome-wide association loci for human diseases and traits, vol.106, pp.9362-9367, 2009.

C. C. Spencer, Z. Su, P. Donnelly, and J. Marchini, Designing genome-wide association studies: sample size, power, imputation, and the choice of genotyping chip, PLoS Genetics, vol.5, issue.5, p.1000477, 2009.

Q. Zhang and J. Ott, Multiple comparison/testing issues, Handbook on Analyzing Human Genetic Data, pp.277-287, 2010.

Y. S. Aulchenko, S. Ripke, A. Isaacs, and C. M. Van-duijn, Genabel: an R library for genome-wide association analysis, Bioinformatics, vol.23, issue.10, pp.1294-1296, 2007.

B. L. Browning, PRESTO: rapid calculation of order statistic distributions and multiple-testing adjusted P-values via permutation for one and two-stage genetic association studies, BMC Bioinformatics, vol.13, issue.9, p.309, 2008.

J. Gonzalez, L. Armengol, X. Sole, R. Guino, J. M. Mercader et al., SNPassoc: an R package to perform whole genome association studies, Bioinformatics, vol.23, pp.644-649, 2007.

K. S. Pollard, S. Dudoit, and M. J. Van-der-laan, Multiple testing procedures: the multtest package and applications to genomics, Bioinformatics and Computational Biology Solutions Using R and Bioconductor, pp.249-271, 2005.

S. Purcell, B. Neale, K. Todd-brown, L. Thomas, M. A. Ferreira et al., PLINK: a toolset for whole-genome association and population-based linkage analysis, American Journal of Human Genetics, vol.81, 2007.

G. Lettre, C. Lange, and J. N. Hirschhorn, Genetic model testing and statistical power in population-based association studies of quantitative traits, Genetic Epidemiology, vol.31, issue.4, pp.358-362, 2007.

R. J. Klein, Power analysis for genome-wide association studies, BMC Genetics, vol.8, issue.58, 2007.

I. Menashe, P. S. Rosenberg, and B. E. Chen, PGA: power calculator for case-control genetic association analyses, BMC Genetics, vol.9, issue.1, p.36, 2008.

J. P. Steibel and G. R. Abecasis, QpowR: Interactive power calculator for two-stage genetic association studies of quantitative traits, 2008.

B. Han, H. M. Kang, and E. Eskin, Rapid and accurate multiple testing correction and power estimation for millions of correlated markers, PLoS Genetics, vol.5, issue.4, p.1000456, 2009.

H. Richard, M. Schulz, and M. Sultan, Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments, Nucleic Acid Res, vol.38, p.112, 2010.

A. Doucet and A. Johansen, A tutorial on Particle Filtering and Smoothing: Fifteen years later, 2008.

P. Nicolas, Transcriptional landscape estimation from tiling array data using a model of signal shift and drift, Bioinformatics, vol.25, pp.2341-2347, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01197505

J. Marioni, RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays, Genome research, vol.18, pp.1509-1517, 2008.

F. Picard, S. Robin, M. Lavielle, C. Vaisse, and J. Daudin, A statistical approach for array CGH data analysis, BMC Bioinformatics, vol.6, p.27, 2005.
URL : https://hal.archives-ouvertes.fr/hal-01222433

A. Olshen, E. Venkatraman, R. Lucito, and M. Wigler, Circular binary segmentation for the analysis of array-based DNA copy number data, Biostatistics, vol.5, issue.4, pp.557-572, 2004.

W. Lai, M. Johnson, R. Kucherlapati, and P. Park, Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data, Bioinformatics, vol.21, issue.19, pp.3763-3770, 2005.

R. Bellman, On the approximation of curves by line segments using dynamic programming, Commun. ACM, vol.4, issue.6, p.284, 1961.

E. Venkatraman and A. Olshen, A faster circular binary segmentation algorithm for the analysis of array CGH data, Bioinformatics, vol.23, issue.6, pp.657-663, 2007.

G. , Pruned dynamic programming for optimal multiple change-point detection, 2010.

D. Chiang, G. Getz, D. Jaffe, M. O'kelly, X. Zhao et al., High-resolution mapping of copy-number alterations with massively parallel sequencing, Nat Meth, vol.6, issue.1, pp.99-103, 2009.

M. Lavielle, Using penalized contrasts for the change-point problem, Signal Processing, vol.85, issue.8, pp.1501-1510, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00070662

J. Bai and P. Perron, Computation and analysis of multiple structural change models, J. Appl. Econ, vol.18, pp.1-22, 2003.

M. Costanzo, A. Baryshnikova, J. Bellay, Y. Kim, E. D. Spear et al., The genetic landscape of a cell, Science, vol.327, issue.5964, pp.425-431, 2010.

S. Bandyopadhyay, M. Mehta, D. Kuo, M. K. Sung, R. Chuang et al., Rewiring of genetic networks in response to DNA damage, Science, vol.330, issue.6009, pp.1385-1389, 2010.

H. E. Burston, L. Maldonado-baez, M. Davey, B. Montpetit, C. Schluter et al., Regulators of yeast endocytosis identified by systematic quantitative analysis, J Cell Biol, vol.185, issue.6, pp.1097-1110, 2009.

S. R. Collins, M. Schuldiner, N. J. Krogan, and J. S. Weissman, A strategy for extracting and analyzing large-scale quantitative epistatic interaction data, Genome Biol, vol.7, issue.7, p.63, 2006.

K. Liolios, I. M. Chen, K. Mavromatis, N. Tavernarakis, P. Hugenholtz et al., The Genomes On Line Database (GOLD) in 2009: status of genomic and metagenomic projects and their associated metadata, Nucleic acids research, vol.38, pp.346-354, 2010.

A. Eyre-walker, The genomic rate of adaptive evolution, Trends in ecology & evolution, vol.21, pp.569-575, 2006.

D. Graur and W. H. Li, Fundamentals of molecular evolution, 2000.

R. A. Studer, S. Penel, L. Duret, and M. Robinson-rechavi, Pervasive positive selection on duplicated and nonduplicated vertebrate protein coding genes, Genome research, vol.18, pp.1393-1402, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00428199

Z. Yang, PAML 4: phylogenetic analysis by maximum likelihood, Molecular Biology and Evolution, vol.24, pp.1586-1591, 2007.

J. G. Glanville, D. Kirshner, N. Krishnamurthy, and K. Sjolander, Berkeley Phylogenomics Group web servers: resources for structural phylogenomic analysis, Nucleic acids research, vol.35, pp.27-32, 2007.

C. Y. Lin, F. K. Lin, C. H. Lin, L. W. Lai, H. J. Hsu et al., POWER: PhylOgenetic WEb Repeater--an integrated and user-optimized framework for biomolecular phylogenetic analysis, Nucleic acids research, vol.33, pp.553-556, 2005.

B. Neron, H. Menager, C. Maufrais, N. Joly, J. Maupetit et al., Mobyle: a new full web bioinformatics framework, vol.25, pp.3005-3011, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01287963

A. Dereeper, V. Guignon, G. Blanc, S. Audic, S. Buffet et al., Phylogeny.fr: robust phylogenetic analysis for the non-specialist, Nucleic acids research, vol.36, pp.465-469, 2008.
URL : https://hal.archives-ouvertes.fr/lirmm-00324099

J. Huerta-cepas, S. Capella-gutierrez, L. P. Pryszcz, I. Denisov, D. Kormes et al., PhylomeDB v3.0: an expanding repository of genome-wide collections of trees, alignments and phylogeny-based orthology and paralogy predictions, Nucleic acids research, vol.39, pp.556-560, 2010.

J. Ruan, H. Li, Z. Chen, A. Coghlan, L. J. Coin et al., Update. Nucleic acids research, vol.36, pp.735-740, 2008.

A. Stern, A. Doron-faigenboim, E. Erez, E. Martz, E. Bacharach et al., Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach, Nucleic acids research, vol.35, pp.506-511, 2007.

W. Delport, A. F. Poon, S. D. Frost, and S. L. Pond, Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology, Bioinformatics, vol.26, pp.2455-2457, 2010.

E. Proux, R. A. Studer, S. Moretti, and M. Robinson-rechavi, Selectome: a database of positive selection, Nucleic acids research, vol.37, pp.404-407, 2009.

J. Tarraga, I. Medina, L. Arbiza, J. Huerta-cepas, T. Gabaldon et al., Phylemon: a suite of web tools for molecular evolution, phylogenetics and phylogenomics, Nucleic acids research, vol.35, pp.38-42, 2007.

P. Flicek, M. R. Amode, D. Barrell, K. Beal, S. Brent et al., Nucleic acids research, vol.39, pp.800-806, 2010.

R. C. Edgar, MUSCLE: a multiple sequence alignment method with reduced time and space complexity, BMC Bioinformatics, vol.5, p.113, 2004.

G. Talavera and J. Castresana, Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments, Systematic Biology, vol.56, pp.564-577, 2007.

N. Eswar, D. Eramian, B. Webb, M. Y. Shen, and A. Sali, Protein structure modeling with MODELLER, 2008.

A. M. Waterhouse, J. B. Procter, D. M. Martin, M. Clamp, and G. J. Barton, Jalview Version 2--a multiple sequence alignment editor and analysis workbench, Bioinformatics, vol.25, pp.1189-1191, 2009.

M. V. Han and C. M. Zmasek, phyloXML: XML for evolutionary biology and comparative genomics, vol.10, p.356, 2009.

A. Herráez, Biomolecules in the computer: Jmol to the rescue, Biochemistry and Molecular Biology Education, vol.34, pp.255-261, 2006.

A. Stabenau, G. Mcvicker, C. Melsopp, G. Proctor, M. Clamp et al., The Ensembl core software libraries, Genome research, vol.14, pp.929-933, 2004.

A. J. Vilella, J. Severin, A. Ureta-vidal, L. Heng, R. Durbin et al., EnsemblCompara GeneTrees: Complete, duplication-aware phylogenetic trees in vertebrates, Genome research, vol.19, pp.327-335, 2009.

M. Suyama, D. Torrents, and P. Bork, PAL2NAL: robust conversion of protein sequence alignments into the corresponding codon alignments, Nucleic acids research, vol.34, pp.609-612, 2006.

S. Guindon, J. F. Dufayard, V. Lefort, M. Anisimova, W. Hordijk et al., New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0, Systematic Biology, vol.59, pp.307-321, 2010.
URL : https://hal.archives-ouvertes.fr/lirmm-00511784

C. M. Zmasek and S. R. Eddy, ATV: display and manipulation of annotated phylogenetic trees, Bioinformatics, vol.17, pp.383-384, 2001.

S. F. Altschul, T. L. Madden, A. A. Schaffer, J. Zhang, Z. Zhang et al., Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Nucleic acids research, vol.25, pp.3389-3402, 1997.

P. W. Rose, B. Beran, C. Bi, W. F. Bluhm, D. Dimitropoulos et al., The RCSB Protein Data Bank: redesigned web site and web services, Nucleic acids research, vol.39, pp.392-401, 2011.

M. Muffato, A. Louis, C. E. Poisnel, and H. R. Crollius, Genomicus: a database and a browser to study gene synteny in modern and ancestral genomes, Bioinformatics, vol.26, pp.1119-1121, 2010.

N. A. Moran, C. D. Dohlen, and P. Baumann, Faster evolutionary rates in endosymbiotic bacteria than in cospeciating insect hosts, J. Mol. Evol, vol.41, pp.727-731, 1995.

F. M. Jiggins, G. D. Hurst, and Z. Yang, Host-symbiont conflicts: positive selection on an outer membrane protein of parasitic but not mutualistic Rickettsiaceae, Mol. Biol. Evol, vol.19, pp.1341-1349, 2002.

A. E. Hirsh and H. B. Fraser, Protein dispensability and rate of evolution, Nature, vol.411, pp.1046-1049, 2001.

H. B. Fraser, A. E. Hirsh, L. M. Steinmetz, C. Scharfe, and M. W. Feldman, Evolutionary rate in the protein interaction network, Science, vol.296, pp.750-752, 2002.

L. Duret and D. Mouchiroud, Determinants of substitution rates in mammalian genes: expression pattern affects selection intensity but not mutation rate, Mol. Biol. Evol, vol.17, pp.68-74, 2000.
URL : https://hal.archives-ouvertes.fr/hal-00427068

E. P. Rocha, The quest for the universals of protein evolution, Trends Genet, vol.22, pp.412-416, 2006.

N. Lartillot and R. Poujol, A phylogenetic model for investigating correlated evolution of substitution rates and continuous phenotypic characters, Mol. Biol. Evol, vol.28, pp.729-744, 2011.

A. L. Koch, Oligotrophs versus copiotrophs. Bioessays, vol.23, pp.657-661, 2001.

H. Bremer and P. P. Dennis, Modulation of cell parameters by growth rate. Escherichia coli and Salmonella: cellular and molecular biology, pp.1553-1569, 1996.

S. Vieira-silva and E. P. Rocha, The systemic imprint of growth and its uses in ecological (meta)genomics, PLoS Genet, vol.6, p.1000808, 2010.
URL : https://hal.archives-ouvertes.fr/pasteur-00488678

P. López-garcía, C. Brochier, D. Moreira, and F. Rodríguez-valera, Comparative analysis of a genome fragment of an uncultivated mesopelagic crenarchaeote reveals multiple horizontal gene transfers, Environ Microbiol, vol.6, issue.1, pp.19-34, 2004.

C. Brochier-armanet, B. Boussau, S. Gribaldo, and P. Forterre, Mesophilic crenarchaeota: proposal for a third archaeal phylum, the Thaumarchaeota, Nature Reviews Microbiology, vol.6, pp.245-252, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00256781

. Kv, F. Dorn, C. Willmund, C. Schwarz, T. Henselmann et al., Chloroplast DnaJ-like proteins 3 and 4 (CDJ3/4) from Chlamydomonas reinhardtii contain redox-active Fe-S clusters and interact with stromal HSP70B, Biochem J, vol.427, issue.2, pp.205-220, 2010.

S. Gribaldo, V. Lumia, R. Creti, E. C. De-macario, A. Sanangelantoni et al., Discontinuous Occurrence of the hsp70 (dnaK) Gene among Archaea and Sequence Features of HSP70 Suggest a Novel Outlook on Phylogenies Inferred from This Protein, J Bacteriol, vol.181, issue.2, pp.434-443, 1999.

. Aj, L. Macario, A. R. Brocchieri, E. Shenoy, and . Conway-de-macario, Evolution of a Protein-Folding Machine: Genomic and Evolutionary Analyses Reveal Three Lineages of the Archaeal hsp70(dnaK) Gene, J Mol Evol, vol.63, issue.1, pp.74-86, 2006.

T. Gabaldón, Large-scale assignment of orthology: back to phylogenetics?, Genome Biol, vol.9, p.235, 2008.

J. F. Dufayard, L. Duret, S. Penel, M. Gouy, F. Rechenmann et al., Tree pattern matching in phylogenetic trees: automatic search for orthologs or paralogs in homologous gene sequence databases, Bioinformatics, vol.21, pp.2596-2603, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00427861

J. Dutheil, S. Gaillard, E. Bazin, S. Glemin, V. Ranwez et al., Bio++: A set of C++ libraries for sequence analysis, phylogenetics, molecular evolution and population genetics, BMC Bioinformatics, vol.7, issue.188, 2006.
URL : https://hal.archives-ouvertes.fr/halsde-00323971

S. Penel, A. M. Arigon, J. F. Dufayard, A. S. Sertier, V. Daubin et al., Databases of homologous gene families for comparative genomics, BMC Bioinformatics, vol.10, issue.S6, 2009.
URL : https://hal.archives-ouvertes.fr/lirmm-00400099

T. Schiex, A. Moisan, and P. Rouzé, Eugène: an eukaryotic gene finder that combines several sources of evidence, LNCS, vol.2066, pp.118-133, 2000.

S. Foissac, J. Gouzy, S. Rombauts, C. Mathe, J. Amselem et al., Genome annotation in plants and fungi: EuGene as a model platform, Current Bioinformatics, vol.3, issue.2, pp.87-97, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02658120

J. Lafferty, A. Mccallum, and F. Pereira, Conditional random fields: Probabilistic models for segmenting and labeling sequence data, Proc. of the Machine Learning International Workshop, pp.282-289, 2001.

T. Schiex, P. Thébault, and D. Khan, Recherche des génes et des erreurs de séquençage dans les génomes bactériens GC-riches, Proc. of JOBIM'2000 (Journées Ouvertes Biologie Informatique Mathématiques), 2000.

T. Schiex, J. Gouzy, A. Moisan, and Y. De-oliveira, FrameD: A flexible program for quality check and gene prediction in prokaryotic genomes and noisy matured eukaryotic sequences, Nucleic Acids Res, vol.31, issue.13, pp.3738-3779, 2003.

E. Rivas and S. R. Eddy, Noncoding RNA gene detection using comparative sequence analysis, BMC Bioinformatics, vol.2, issue.8, 2001.

T. Flutre, E. Duprat, C. Feuillet, and H. Quesneville, Considering transposable element diversification in de novo annotation approaches, PLoS ONE, vol.6, issue.1, p.16526, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00956366

H. Quesneville, C. M. Bergman, O. Andrieu, D. Autard, and D. Nouaud, Combined evidence annotation of transposable elements in genome sequences, PLoS comput. Biol, vol.1, issue.2, p.22, 2005.
URL : https://hal.archives-ouvertes.fr/inserm-00000104

S. Foissac, J. Gouzy, S. Rombauts, C. Mathé, J. Amselem et al., Genome Annotation in Plants and fungi : Eugene as a model platform, Current Bioinformatics, vol.3, issue.2, pp.87-97, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02658120

T. Rouxel, J. Grandaubert, J. Hane, C. Hoede, A. Van-de-wouw et al., Effector diversification within compartments of the Leptosphaeria maculans genome affected by Repeat-Induced Point mutations, Nat. Comms, vol.2, p.202, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00698420

W. Marande and G. Burger, Mitochondrial DNA as a genomic jigsaw puzzle, Science, vol.318, p.415, 2007.

C. Vlcek, W. Marande, S. Teijeiro, J. Lukes, and G. Burger, Systematically fragmented genes in a multipartite mitochondrial genome, Nucleic Acids Res, vol.39, pp.979-88, 2011.

S. Kumar and M. L. Blaxter, Comparing de novo assemblers for 454 transcriptome data, BMC Genomics, vol.11, p.571, 2010.

E. A. Worthey and P. J. Myler, Protozoan genomes: gene identification and annotation, Int J Parasitol, vol.35, pp.495-512, 2005.

R. Salavati and H. S. Najafabadi, Sequence-based functional annotation: what if most of the genes are unique to a genome?, Trends Parasitol, vol.26, pp.225-234, 2010.

P. Keeling, G. Burger, D. Durnford, B. Lang, R. Lee et al., The tree of eukaryotes, Trends Ecol Evol (Amst), vol.20, pp.670-676, 2005.

, Millennium Ecosystem Assessment (MEA), 2005.

P. Sukhdev, The Economics of Ecosystems and Biodiversity (TEEB) interim Report, 2008.

O. P. Ostermann, The need for management of nature conservation sites designated under Natura, Journal of Applied Ecology, vol.35, pp.968-97, 1998.

T. Berners-lee, J. Hendler, and O. Lassila, The semantic web, Scientific American, pp.29-37, 2001.

C. Bizer, T. Heath, and T. Berners-lee, Linked Data -The Story So Far, International Journal on Semantic Web and Information Systems (IJSWIS), vol.5, issue.3, pp.1-22, 2009.

O. J. Reichman, M. B. Jones, and M. P. Schilldhauer, Challenges and Opportunities of Open Data in Ecology, Science, vol.331, pp.703-705, 2011.

O. Coullet, A. Sahl, J. Chabalier, and O. Rovellotti, ecoRelevé: an open source response to the biodiversity crisis. Proceedings of the conference for Open Source Geospatial Software (FOSS4G), 2010.

T. Catapano, D. Hobern, H. Lapp, R. A. Morris, N. Morrison et al., Recommendations for the Use of Knowledge Organisation System by GBIF, 2011.

M. Iliff, L. Salas, E. Inzunza, G. Ballard, D. Lepage et al., The avian knowledge network: a partnership to organize, analyse, and visualize bird observation data for education, conservation, research, and land management, Proceedings of the fourth Inrternational Partners in Filght Conference: Tundra to Tropics, pp.365-376

R. Kipré, O. Coullet, A. Sahl, J. Chabalier, C. Duval et al., Pocket eRelevé : nouvelle approche de collecte de données sur le terrain, Géomatique Expert, vol.69, pp.24-27, 2009.

G. Ontology,

J. Chabalier, EcoOnto : une ontologie pour la biodiversité. Acte du colloque national d'écologie scientifique, 2010.

J. Madin, S. Bowers, M. Shildhauer, S. Krivov, D. Pennington et al., An ontology for describing and synthesizing ecological observation data, Ecological Informatics, vol.2, pp.279-296, 2007.

E. V. Koonin, L. Aravind, and A. S. Kondrashov, The impact of comparative genomics on our understanding of evolution, Cell, vol.101, pp.573-576, 2000.

C. T. Lopes, M. Franz, F. Kazi, S. L. Donaldson, Q. Morris et al., Cytoscape Web: an interactive webbased network browser, Bioinformatics, vol.26, pp.2347-2348, 2010.

B. Medea and . Institute,

P. Lechat, L. Hummel, S. Rousseau, and I. Moszer, GenoList: an integrated environment for comparative analysis of microbial genomes, Nucleic Acids Res, vol.36, pp.469-474, 2008.
URL : https://hal.archives-ouvertes.fr/pasteur-02634892

J. Felsenstein, Confidence Limits on Phylogenies: An Approach Using the Bootstrap, vol.39, pp.783-791, 1985.

E. Susko, Bootstrap support is not first-order correct, Systematic Biology, vol.58, pp.211-233, 2009.

T. A. Heath, S. M. Hedtke, and D. M. Hillis, Taxon sampling, the accuracy of phylogenetic analyses, J. Mol. Evol, vol.46, pp.239-257, 2008.

F. R. Hampel, The influence curve and its role in robust estimation, JASA, vol.69, pp.383-393, 1974.

A. Bar-hen, M. Mariadassou, M. Poursat, and P. Vandenkoornhuyse, Influence function for robust phylogenetic reconstructions, Molecular Biology and Evolution, vol.25, pp.869-873, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00312860

M. Mariadassou, A. Bar-hen, and H. Kishino, Taxon Influence Index, 2011.

M. Mariadassou and A. ,

F. Ababneh, L. S. Jermiin, C. Ma, and J. Robinson, Matched-pairs tests of homogeneity with applications to homologous nucleotide sequences, Bioinformatics, vol.22, pp.1225-1256, 2006.

C. Ané, B. Larget, D. A. Baum, S. D. Smith, and A. Rokas, Bayesian estimation of concordance among gene trees, Mol. Biol. Evol, vol.24, pp.412-438, 2007.

M. Anisimova and O. Gascuel, Approximate Likelihood-ratio test for branches: a fast, accurate, and powerful alternative, Syst. Biol, vol.55, pp.539-52, 2006.
URL : https://hal.archives-ouvertes.fr/lirmm-00136658

S. Blanquart and N. Lartillot, A Bayesian compound stochastic process for modelling nonstationary and nonhomogeneous sequence evolution, Mol. Biol. Evol, vol.23, pp.2058-71, 2006.

B. Bousseau and M. Gouy, Efficient likelihood computations with non-reversible models of evolution, Syst. Biol, vol.55, pp.756-68, 2006.

J. G. Burleigh, A. C. Driskell, and M. J. Sanderson, Supertree bootstrapping methods for assessing phylogenetic variation among genes in genome-scale data sets, Syst. Biol, vol.55, pp.426-466, 2006.

S. Capella-gutiérez, J. M. Silla-martínez, and T. Gabaldón, trimAl: a tool for automated alignment triming in largescale phylogenetic analyses, Bioinformatics, vol.25, pp.1972-1975, 2009.

J. Castresana, Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis, Mol. Biol. Evol, vol.17, pp.540-52, 2000.

A. Criscuolo and C. J. Michel, Phylogenetic inference with weighted codon evolutionary distances, J. Mol. Evol, vol.68, pp.377-92, 2009.

A. Criscuolo and S. Gribaldo, BMGE (Block Mapping and Gathering with Entropy): a new software for selection of phylogenetic informative regions from multiple sequence alignments, BMC Evol. Biol, vol.10, p.210, 2010.
URL : https://hal.archives-ouvertes.fr/pasteur-02445904

T. M. Embley, M. Van-der-giezen, D. S. Horner, P. L. Dyal, and P. G. Foster, Mitochondria and hydrogenosomes are two forms of the same fundamental organelle, Philos. Trans. R. Soc. Lond. B. Biol. Sci, vol.358, pp.191-203, 2003.

A. W. Dress, C. Flamm, G. Fritzsch, S. Grünewald, M. Kruspe et al., Noisy: Identification of problematic columns in multiple sequence alignments, Algorithms Mol. Biol, vol.3, p.7, 2008.

J. Felsenstein, Evolutionary tree from DNA sequences:a maximum likelihood approach, J.Mol.Evol, vol.17, pp.368-76, 1981.

J. Felsenstein, Confidence limits on phylogenies: an approach using the bootstrap, vol.39, pp.783-91, 1985.

P. G. Foster, Modeling compositional heterogeneity, Syst. Biol, vol.53, pp.485-95, 2004.

P. G. Foster and D. A. Hyckey, Compositional bias may affect both DNA-based and protein-based phylogenetic reconstructions, J. Mol. Evol, vol.48, pp.284-90, 1999.

N. Galtier and M. Gouy, Inferring phylogenies from DNA sequences of unequal base composition, Proc. Natl. Acad. Sci. USA, vol.92, pp.11317-11338, 1995.

N. Galtier and M. Gouy, Inferring pattern and process: maximum-likelihood implementation of a nonhomogeneous model of DNA sequence evolution for phylogenetic analysis, Mol. Biol. Evol, vol.15, pp.871-880, 1998.
URL : https://hal.archives-ouvertes.fr/hal-00428472

V. Gowri-shankar and M. Rattray, A reversible jump method for Bayesian phylogenetic inference with a nonhomogeneous substitution model, Mol. Biol. Evol, vol.24, pp.1286-99, 2007.

S. Guindon and O. Gascuel, A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood, Syst. Biol, vol.52, pp.696-704, 2003.

I. Hrdy, R. P. Hirt, P. Dolezal, L. Bardonova, P. G. Foster et al., Trichomonas hydrogenosomes contain the NADH deshydrogenase module of mitochondria complex I, Nature, vol.432, pp.618-640, 2004.

J. Hughes, S. J. Longhorn, A. Papadopoulou, K. Theodorides, A. Riva et al., Dense taxonomic EST sampling and its applications for molecular systematics of the Coleoptera (beetles), vol.23, pp.268-78, 2006.

T. Hunt, J. Bergsten, Z. Levkanicova, A. Papadopoulou, O. S. John et al., A comprehensive phylogeny of beetles reveals the evolutionary origins of a superradiation, vol.318, pp.1913-1919, 2007.

L. S. Jermiin, S. Y. Ho, F. Ababneh, J. Robinson, and A. W. Larkum, The biasing effect of compositional heterogeneity on phylogenetic estimates may be underestimated, Syst. Biol, vol.53, pp.638-681, 2004.

J. A. Lake, The order of sequence alignment can bias the selection of tree topology, Mol.Biol.Evol, vol.8, pp.378-85, 1991.

J. A. Lake, Reconstructing evolutionary trees from DNA and protein sequences: paralinear distances, Proc. Natl. Acad. Sci. USA, vol.91, pp.1455-1464, 1994.

P. J. Lockhart, M. A. Steel, M. D. Hendy, and D. Penny, Recovering evolutionary trees under a more realistic model of sequence evolution, Mol. Biol. Evol, vol.11, pp.605-617, 1994.

D. A. Morrison and J. T. Ellis, Effects of nucleotide sequence alignment on phylogeny estimation: a case study on 18S rDNAs of Apicomplexa, Mol. Biol. Evol, vol.14, pp.428-469, 1997.

T. H. Ogden and M. S. Rosenberg, Multiple sequence alignment accuracy and phylogenetic inference, Syst. Biol, vol.55, pp.314-342, 2006.

O. Penn, E. Privman, G. Landan, D. Graur, and T. Pupko, An alignment confidence score capturing robustness to guide tree uncertainty, Mol. Biol. Evol, vol.27, pp.1759-67, 2010.

M. J. Phillips, F. Delsuc, and D. Penny, Genome-scale phylogeny and the detection of systematic biases, Mol. Biol. Evol, vol.21, pp.1455-1463, 2004.
URL : https://hal.archives-ouvertes.fr/halsde-00193019

F. Ren, H. Tanaka, and Z. Yang, An empirical examination of the utility of codon-substitution models in phylogeny reconstruction, Syst. Biol, vol.54, pp.808-826, 2005.

R. Rodríguez, J. L. Oliver, A. Marin, and J. R. Medina, The general stochastic model of nucleotide substitution, J. Theor. Biol, vol.142, pp.485-501, 1990.

A. Rokas, B. L. Williams, N. King, and S. B. Carroll, Genome-scale approaches to resolving incongruence in molecular phylogenies, Nature, vol.425, pp.798-804, 2003.

A. Stuart, A test for homogeneity of the marginal distributions in a two way classification, Biometrika, vol.42, pp.412-418, 1955.

N. C. Sheffield, H. Song, S. L. Cameron, and M. F. Whiting, Nonstationary evolution and compositional heterogeneity in beetle mitochondrial phylogenomics, Syst. Biol, vol.58, pp.381-94, 2009.

E. Susko and A. J. Roger, On reduced amino acid alphabets for phylogenetic inference, Mol. Biol. Evol, vol.24, pp.2139-50, 2007.

G. Talavera and J. Castresana, Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments, Syst. Biol, vol.56, pp.564-77, 2007.

K. Tamura and S. Kumar, Evolutionary distance estimation under heterogeneous substitution pattern among lineages, Mol. Biol. Evol, vol.19, pp.1727-1763, 2002.

R. Tarrío, F. Rodríguez-trelles, and F. J. Ayala, Shared nucleotide composition biases among species and their impact on phylogenetic reconstructions of the Drosophilidae, Mol. Biol. Evol, vol.18, pp.1464-73, 2001.

D. J. Taylor and W. H. Piel, An assessment of accuracy, error, and conflict with support values from genome-scale phylogenetic data, Mol. Biol. Evol, vol.21, pp.1534-1541, 2004.

H. Uesaka, Validity and applicability of several tests for comparing marginal distributions of a square table with ordered categories, Behaviormetrika, vol.30, pp.65-78, 1991.

Z. Yang, Estimating the pattern of nucleotide substitution, J. Mol. Evol, vol.39, pp.105-116, 1994.

R. C. Jansen and J. P. Nap, Genetical genomics: the added value from segregation, TRENDS in Genetics, vol.17, pp.388-391, 2001.

R. B. Brem, G. Yvert, R. Clinto, and L. Kruglyak, Genetic Dissection of Transcriptional Regulation in Budding Yeast, Science, vol.296, pp.752-755, 2002.

E. E. Schadt, S. A. Monks, T. A. Drake, A. J. Lusis, and N. Che, Genetics of gene expression surveyed in maize, mouse and man, Nature, vol.422, pp.297-302, 2003.

S. A. Monks, A. Leonardson, H. Zhu, P. Cundiff, and P. Pietrusiak, Genetic inheritance of gene expression in human cell lines, Am. J. Hum. Genet, vol.75, pp.1094-1105, 2004.

M. Morley, C. M. Molony, T. M. Weber, J. L. Devlin, K. G. Ewens et al., Genetic analysis of genome-wide variation in human gene expression, Nature, vol.430, pp.743-747, 2004.

C. Shi, A. Uzarowska, M. Ouzunova, and M. Landbeck, Identification of candidate genes associated with cell wall digestibility and eQTL (expression quantitative trait loci) analysis in a Flint × Flint maize recombinant inbred line population, BMC Genomics, vol.8, p.22, 2007.

G. Le-mignon, C. Desert, F. Pitel, S. Leroux, and O. Demeure, Using transcriptome profiling to characterize QTL regions on chicken chromosome 5, BMC Genomics, vol.10, p.575, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00730106

S. Ponsuksili, E. Murani, M. Schwerin, K. Schellander, and K. Wimmers, Identification of expression QTL (eQTL) of genes expressed in porcine M. longissimus dorsi and associated with meat quality traits, BMC Genomics, vol.8, p.22, 2010.

Y. L. Bras, N. Dechamp, J. Montfort, A. L. Cam, F. Krieg et al., Acclimation to seawater in rainbow trout: QTL/eQTL approach for plasmatic ions and gill tissue, Proc. 9th WCGALP, pp.4-120, 2010.

G. Le-mignon, Y. Blum, O. Demeure, C. Diot, E. L. Bihan-duval et al., Apports de la génomique fonctionnelle à la cartographie fine de QTL, INRA Prod. Anim, vol.23, issue.4, pp.343-358, 2010.

J. D. Storey, J. M. Akey, and L. Kruglyak, Multiple locus linkage analysis of genomewide in yeast, PLoS Biol, vol.3, issue.8, p.267, 2005.

P. Wang, J. A. Dawson, M. P. Keller, B. S. Yandell, and N. A. Thornberry, A model approach for expression quantitative trait loci (eQTL) mapping, Genetics, vol.187, pp.611-621, 2010.

G. Y. Sun and P. Schliekelman, A genetical genomics approach to genome scans increases power for QTL mapping, Genetics, vol.110, p.123968, 2010.

G. A. Walling, C. S. Haley, M. Perez-enciso, R. Thompson, and P. M. Visscher, On the mapping of quantitative trait loci at marker and non-marker locations, Genetical Research, vol.79, pp.97-106, 2002.
URL : https://hal.archives-ouvertes.fr/hal-02678028

X. Q. Wang, J. M. Elsen, H. Gilbert, C. Moreno, O. Filangi et al., The repercussions of statistical properties of interval mapping methods on eQTL detection
URL : https://hal.archives-ouvertes.fr/hal-01193475

C. J. Jiang and Z. B. Zeng, Multiple trait analysis of genetic mapping for quantitative trait loci, Genetics, vol.140, pp.1111-1127, 1995.

S. A. Knott and C. S. Haley, Multitrait least squares for quantitative trait loci detection, Genetics, vol.156, pp.899-911, 2000.

E. E. Schadt, J. Lamb, X. Yang, J. Zhu, and S. Edwards, An integrative genomics approach to infer causal associations between gene expression and disease, Nature genetics, vol.37, pp.710-717, 2005.

H. Gilbert and P. Roy, Comparison of three multitrait methods for QTL detection, Genet. Sel. Evol, vol.35, pp.281-304, 2003.
URL : https://hal.archives-ouvertes.fr/hal-02830989

H. Gilbert and P. Roy, Methods for the detection of multiple linked QTL applied to a mixture of full and half sib families, Genet. Sel. Evol, vol.39, pp.139-158, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00894583

D. C. Kulp and M. Jagalur, Causal inference of regulator-target pairs by gene mapping of phenotypes, BMC genomics, vol.7, issue.125, 2006.

R. H. Li, S. W. Tsaih, K. Shockley, I. M. Stylianou, and J. , Structural model analysis of multiple quantitative traits, PLos Genetics, vol.2, p.114, 2006.

E. S. Lander and D. Botstein, Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps, Genetics, vol.121, pp.185-191, 1989.

C. S. Haley and S. A. Knott, A simple regression method for mapping quantitative trait loci in line crosses using flanking markers, Heredity, vol.69, pp.315-324, 1992.

A. Legarra and R. L. Fernando, Linear models for joint association and linkage QTL mapping, Genet Sel Evol, vol.41, p.43, 2009.
URL : https://hal.archives-ouvertes.fr/hal-02667504

J. M. Elsen, O. Filangi, H. Gilbert, P. L. Roy, and C. Moreno, A fast algorithm for estimating transmission probabilities in QTL detection designs with dense maps, Genet Sel Evol, vol.41, p.50, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01193461

H. Gilbert, P. L. Roy, C. Moreno, D. Robelin, and J. M. Elsen, QTLMAP, a software for QTL detection in outbred population, Annals of Human Genetics, vol.72, issue.5, p.694, 2008.

H. Gilbert and P. Roy, Methods for the detection of multiple linked QTL applied to a mixture of full and half sib families, Genet Sel Evol, vol.39, issue.2, pp.139-58, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00894583

C. R. Moreno, J. M. Elsen, P. L. Roy, and V. Ducrocq, Interval mapping methods for detecting QTL affecting survival and time-to-event phenotypes, Genet. Res. Camb, vol.85, pp.139-149, 2005.
URL : https://hal.archives-ouvertes.fr/hal-02675686

B. Goffinet, P. L. Roy, D. Boichard, J. M. Elsen, and B. Mangin, Alternative models for QTL detection in livestock. III. Heteroskedastic model and models corresponding to several distributions of the QTL effect, Genet. Sel. Evol, vol.31, pp.341-350, 1999.
URL : https://hal.archives-ouvertes.fr/hal-00199719

B. Mangin, B. Goffinet, P. L. Roy, D. Boichard, and J. M. Elsen, Alternative models for QTL detection in livestock. II. Likelihood approximations and sire marker genotype estimations, Genet. Sel. Evol, vol.31, pp.225-237, 1999.
URL : https://hal.archives-ouvertes.fr/hal-00199719

J. M. Elsen, B. Mangin, B. Goffinet, D. Boichard, and P. Roy, Alternative models for QTL detection in livestock. I. General introduction, Genet. Sel. Evol, vol.31, pp.213-224, 1999.
URL : https://hal.archives-ouvertes.fr/hal-00199719

J. H. Nadeau and B. A. Taylor, Lengths pf chromosomal segments conserved since divergence of man and mouse, Proc Natl Acad Sci U S A, vol.81, pp.814-818, 1984.

P. Pevzner and G. Tesler, Human and mouse genomic sequences reveal extensive breakpoint reuse in mammalian evolution, Proc Natl Acad Sci U S A, vol.100, pp.7672-7677, 2003.

Q. Peng, P. A. Pevzner, and G. Tesler, The fragile breakage model versus random breakage models of chromosome evolution, PloS Comput Biol, vol.2, p.4, 2006.

D. M. Larkin, G. Pape, R. Donthu, L. Auvil, M. Wedge et al., Breakpoint regions and homologous synteny blocks in chromosomes have different evolutionary histories, Genome Res, vol.19, pp.770-777, 2009.

C. Lemaitre, L. Zaghloul, M. Sagot, C. Gautier, A. Arneodo et al., Analysis of fine-scale mammalian evolutionary breakpoints provides new insight into their relation to genome organisation, BMC Genomics, vol.10, pp.335-346, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00784451

M. Muffato, A. Louis, and H. R. Crollius, AGORA: an Ancestral Gene Order Reconstruction Algorithm

M. Huvet, S. Nicolay, M. Touchon, B. Audit, Y. D'aubenton-carafa et al., Human gene organization driven by the coordination of replication and transcription, Genome Res, vol.17, pp.1278-1285, 2007.
URL : https://hal.archives-ouvertes.fr/ensl-00198451

J. Schacherer, J. A. Shapiro, D. M. Ruderfer, and L. Kruglyak, Comprehensive polymorphism survey elucidates population structure of Saccharomyces cerevisiae, Nature, vol.458, issue.7236, pp.342-345, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00370158

G. Liti, G. , D. M. Carter, A. M. Moses, J. Warringer et al., Population genomics of domestic and wild yeasts, Nature, vol.458, issue.7236, pp.337-341, 2009.

. The-génolevures-consortium, Comparative genomics of protoploid Saccharomycetaceae, Genome Res, vol.19, pp.1696-1709, 2009.

R. Li, C. Yu, Y. Li, T. W. Lam, S. M. Yiu et al., SOAP2: an improved ultrafast tool for short read alignment, Bioinformatics, vol.25, issue.15, pp.1966-1967, 2009.

R. Li, Y. Li, X. Fang, H. Yang, J. Wang et al., SNP detection for massively parallel wholegenome resequencing, Genome Res, vol.19, issue.6, pp.1124-1132, 2009.

J. K. Pritchard, M. Stephens, and P. Donnelly, Inference of population structure using multilocus genotype data, Genetics, vol.155, pp.945-959, 2000.

G. R. Cornelis, The type III secretion injectisome, Nature Review Microbiology, vol.4, issue.11, pp.811-836, 2006.

C. Matz, A. M. Moreno, M. Alhede, M. Manefield, A. R. Hauser et al., Pseudomonas aeruginosa uses type III secretion system to kill biofilm-associated amoebae, The ISME Journal, vol.2, issue.8, pp.843-52, 2008.

S. A. Clock, P. J. Planet, B. A. Perez, and D. H. Figurski, Outer membrane components of the Tad (tight adherence) secreton of Aggregatibacter actinomycetemcomitans, Journal of Bacteriology, vol.190, issue.3, pp.980-90, 2008.

H. Van-megen, S. Van-den-elsen, M. Holterman, G. Karssen, P. Mooyman et al., A phylogenetic tree of nematodes based on about 1200 full-length small subunit ribosomal DNA sequences, Nematology, vol.11, pp.927-950, 2009.

P. Abad, J. Gouzy, J. Aury, P. Castagnone-sereno, E. G. Danchin et al.,

P. Markov, G. Mcveigh, J. Pesole, M. Poulain, E. Robinson-rechavi et al., Genome sequence of the metazoan plant-parasitic nematode Meloidogyne incognita, Nat. Biotechnol, vol.26, pp.909-915, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01189285

C. H. Opperman, D. M. Bird, V. M. Williamson, D. S. Rokhsar, M. Burke et al.,

. Windham, Sequence and genetic map of Meloidogyne hapla: A compact nematode genome for plant parasitism, Proc. Natl. Acad. Sci. U.S.A, vol.105, pp.14802-14807, 2008.

L. Li, C. J. Stoeckert, and D. S. Roos, OrthoMCL: identification of ortholog groups for eukaryotic genomes

, Genome Res, vol.13, pp.2178-2189, 2003.

A. J. Enright, S. Van-dongen, and C. A. Ouzounis, An efficient algorithm for large-scale detection of protein families, Nucleic Acids Res, vol.30, pp.1575-1584, 2002.

S. F. Altschul, T. L. Madden, A. A. Schäffer, J. Zhang, Z. Zhang et al., Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Nucleic Acids Res, vol.25, pp.3389-3402, 1997.

R. Winnenburg, M. Urban, A. Beacham, T. K. Baldwin, S. Holland et al., PHI-base update: additions to the pathogen host interaction database, Nucleic Acids Res, vol.36, pp.572-578, 2008.

J. Parkinson, C. Whitton, R. Schmid, M. Thomson, and M. Blaxter, NEMBASE: a resource for parasitic nematode ESTs, Nucleic Acids Res, vol.32, pp.427-457, 2004.

R. D. Finn, J. Mistry, J. Tate, P. Coggill, A. Heger et al., The Pfam protein families database, Nucleic Acids Res, vol.38, pp.211-233, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01294685

M. Ashburner, C. A. Ball, J. A. Blake, D. Botstein, H. Butler et al., Gene ontology: tool for the unification of biology. The Gene Ontology Consortium, Nat. Genet, vol.25, pp.25-29, 2000.

O. Emanuelsson, S. Brunak, G. Heijne, and H. Nielsen, Locating proteins in the cell using TargetP, SignalP and related tools, Nat Protoc, vol.2, pp.953-971, 2007.

A. Krogh, B. Larsson, G. Heijne, and E. L. Sonnhammer, Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes, J. Mol. Biol, vol.305, pp.567-580, 2001.

C. Vens, M. Rosso, and E. G. Danchin, Identifying discriminative classification-based motifs in biological sequences, Bioinformatics, vol.27, pp.1231-1238, 2011.
URL : https://hal.archives-ouvertes.fr/hal-02652585

S. Haider, B. Ballester, D. Smedley, J. Zhang, P. Rice et al., BioMart Central Portal--unified access to biological data, Nucleic Acids Res, vol.37, pp.23-30, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01615159

G. Bouvier, N. Evrard-todeschi, J. Girault, and G. Bertho, Automatic clustering of docking poses in virtual screening process using self-organizing map, Bioinformatics, vol.26, pp.53-60, 2010.

T. Kohonen, Self-Organizing Maps. Springer Series in Information Sciences, 2001.

E. V. Samsonova, J. N. Kok, and A. P. Ijzerman, TreeSOM: Cluster analysis in the self-organizing map, Neural Netw, vol.19, pp.935-949, 2006.

N. Huang, B. K. Shoichet, and J. J. Irwin, Benchmarking sets for molecular docking, J. Med. Chem, vol.49, pp.6789-6801, 2006.

, Tripos International, 1699 South Hanley Rd

L. Coin, A. Bateman, and R. Durbin, Enhanced protein domain discovery using taxonomy, BMC Bioinf, vol.5, p.56, 2004.

I. Alam, S. Hubbard, S. Olivier, and M. Rattray, A kingdom-specific protein domain HMM library for improved annotation of fungal genomes, BMC Genomics, vol.8, p.97, 2007.

S. Le and O. Gascuel, An improved general amino acid replacement matrix, MBE, vol.25, issue.7, pp.1307-1320, 2008.
URL : https://hal.archives-ouvertes.fr/lirmm-00324106

N. Terrapon, O. Gascuel, É. Maréchal, and L. Bréhélin, Detection of new protein domains using co-occurrence: application to Plasmodium falciparum, Bioinformatics, vol.25, issue.23, pp.3077-3083, 2009.
URL : https://hal.archives-ouvertes.fr/lirmm-00431171

S. Turner, K. M. Pryer, V. P. Miao, and J. D. Palmer, Investigating deep phylogenetic relationships among cyanobacteria and plastids by small subunit rRNA sequence analysis, J. Eukaryot. Microbiol, vol.46, pp.327-365, 1999.

N. Rodriguez-ezpeleta, H. Brinkmann, S. C. Burey, B. Roure, G. Burger et al., Monophyly of primary photosynthetic eukaryotes : green plants, red algae, and glaucophytes, Curr. Biol, vol.25, pp.1325-1355, 2005.

H. Shimodaira and M. Hasegawa, Multiple comparisons of log-likelihoods with applications to phylogenetic inference, Mol. Biol. Evol, vol.16, pp.1114-1120, 1999.

A. Criscuolo and S. Gribaldo, BMGE (Block Mapping and Gathering with Entropy): a new software for selection of phylogenetic informative regions from multiple sequence alignments, BMC Evol. Biol, vol.10, p.210, 2010.
URL : https://hal.archives-ouvertes.fr/pasteur-02445904

E. Susko and A. J. Roger, On reduced amino acid alphabets for phylogenetic inference, Mol. Biol. Evol, vol.24, pp.2139-50, 2007.

S. Guindon and O. Gascuel, A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood, Syst. Biol, vol.52, pp.696-704, 2003.

D. A. Morrison, Increasing the efficiency of searches for the Maximum Likelihood tree in a phylogenetic analysis of up to 150 nucleotide sequences, Syst. Biol, vol.56, pp.988-1010, 2007.

P. Deschamps and D. Moreira, Signal conflicts in the phylogeny of the primary photosynthetic eukaryotes, Mol. Biol. Evol, vol.26, pp.2745-53, 2009.

H. Shimodaira, An approximately unbiased test of phylogenetic tree selection, Syst. Biol, vol.51, pp.492-508, 2002.

O. Deusch, G. Landan, M. Roettger, N. Gruenheit, K. V. Kowallik et al., Genes of cyanobacterial origin in plant nuclear genomes point to a heterocyst-forming plastid ancestor, Mol. Biol. Evol, vol.25, pp.748-61, 2008.

R. Rippka, J. Deruelles, J. B. Waterbury, M. Herdman, and R. Y. Stanier, Generic assignments, strain histories and properties of pure cultures of Cyanobacteria, J. Gen. Microbiol, vol.111, pp.1-61, 1979.

P. Medawar, An Unsolved Problem of Biology, 1952.

T. B. Kirkwood, Evolution of ageing, Nature, vol.31, pp.301-304, 1977.

Y. Suzuki and T. F. Gojobori, A method for detecting positive selection at single amino acid sites, Molecular Biology and Evolution, vol.16, pp.1315-1328, 1999.

M. Kimura, The neutreal theory of neutral evolution Cambridge, 1983.

N. Lartillot and R. Poujol, A phylogenetic model for investigating correlated evolution of substitution rates and continuous phenotypic characters, Molecular Biology and Evolution, vol.28, issue.1, pp.729-773, 2011.

V. Ranwez, F. Delsuc, S. Ranwez, K. Belkhir, M. Tilak et al., A database of orthologous genomic markers for placental mammal phylogenetics, BMC Evolutionary Biology, vol.7, p.241, 2007.
URL : https://hal.archives-ouvertes.fr/halsde-00315511

J. P. De-magalhaes and J. Costa, A database of vertebrate longevity records and their relation to other life-history traits, Journal of Evolutionary Biology, vol.22, issue.8, pp.1770-1774, 2009.

T. Janssen, E. Meelkop, M. Lindemans, K. Verstraelen, S. Husson et al., Discovery of a cholecystokinin-gastrin-like signaling system in nematodes, Endocrinology, vol.149, pp.2826-2839, 2008.

M. Lindemans, F. Liu, T. Janssen, S. Husson, I. Metrens et al., Adipokinetic hormone signaling through the gonadotropin-releasing hormone receptor modulates egg-laying in Caenorhabditis elegans, Proc Natl Acad Sci, vol.106, pp.1642-1647, 2009.

A. Nathoo, R. Moeller, B. Westlund, and A. Hart, Identification of neuropeptide-like protein gene families in Caenorhabditis elegans and other species, Proc Natl Acad Sci, vol.98, pp.14000-14005, 2001.

R. Fredriksson, M. Lagerström, L. Lundin, and H. Schiöth, The G-protein-coupled receptors in the human genome form five main families. Phylogenetic analysis, paralogon groups, and fingerprints, Mol Pharmacol, vol.63, pp.1256-1272, 2003.

S. Guindon and O. Gascuel, A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood, Syst Biol, vol.52, pp.696-704, 2003.

O. Mirabeau, E. Perlas, C. Severini, E. Audero, R. Possenti et al., Identification of novel peptide hormones in the human proteome by hidden Markov model screening, Genome Res, vol.17, pp.320-327, 2007.
URL : https://hal.archives-ouvertes.fr/lirmm-00137629

K. Tessmar-raible, F. Raible, F. Christodoulou, K. Guy, M. Rembold et al., Conserved sensory-neurosecretory cell types in annelid and fish forebrain: insights into hypothalamus evolution, Cell, vol.129, pp.1389-1400, 2007.

O. Hobert, Regulatory logic of neuronal diversity: terminal selector genes and selector motifs, Proc Natl Acad Sci U S A, vol.105, 2008.

H. Bondell and B. Reich, Simultaneous regression shrinkage, variable selection and supervised clustering of predictors with OSCAR, Biometrics, vol.64, pp.115-123, 2008.

A. Dempster, N. Laird, and D. Rubin, Maximum likelihood from incomplete data via the EM algorithm, J. Roy. Statist. Soc, vol.39, pp.1-38, 1977.

G. Govaert and M. Nadif, An EM algorithm for the block mixture model, IEEE Trans. Pattern Anal. Machine Intel, vol.27, pp.643-647, 2005.

R. Levine and G. Casella, Implementations of the Monte Carlo EM algorithm, Journal of Computational and Graphical Statistics, vol.10, pp.422-439, 2001.

M. Jordan, Z. Ghahramani, T. Jaakkola, and L. Saul, An introduction to variational methods for graphical models, Mach. Learn, vol.37, pp.183-233, 1999.

S. Kim and E. Xing, Feature Selection via Block-Regularized Regression, Proceedings of the 24th Conference on Uncertainty in AI (UAI), 2008.

P. J. Goulder and D. I. Watkins, HIV and SIV CTL escape: implications for vaccine design, Nature reviews. Immunology, vol.4, pp.630-640, 2004.

D. L. Robertson, B. H. Hahn, and P. M. Sharp, Recombination in AIDS viruses, Journal of molecular evolution, vol.40, pp.249-259, 1995.

J. M. Carlson, Z. L. Brumme, C. M. Rousseau, C. J. Brumme, P. Matthews et al., Phylogenetic dependency networks: inferring patterns of CTL escape and codon covariation in HIV-1 Gag, PLoS computational biology, vol.4, p.1000225, 2008.

C. B. Moore, M. John, I. R. James, F. T. Christiansen, C. S. Witt et al., Evidence of HIV-1 Adaptation to HLA-Restricted Immune Responses at a Population Level, Science, vol.296, pp.1439-1443, 2002.

A. L. Halpern and W. J. Bruno, Evolutionary distances for protein-coding sequences: modeling site-specific residue frequencies, Molecular biology and evolution, vol.15, pp.910-917, 1998.

S. V. Muse and B. S. Gaut, A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome, Molecular biology and evolution, vol.11, pp.715-724, 1994.

N. Rodrigue, H. Philippe, and N. Lartillot, Mutation-selection models of coding sequence evolution with siteheterogeneous amino acid fitness profiles, Proceedings of the National Academy of Sciences of the United States of America, vol.107, pp.4629-4634, 2010.

Y. Fujii, T. Shimizu, T. Toda, M. Yanagida, and T. Hakoshima, Structural basis for the diversity of DNA recognition by bZIP transcription factors, Nat Struct Biol, vol.7, pp.889-893, 2000.

G. Lelandais, V. Tanty, C. Geneix, C. Etchebest, C. Jacq et al., Genome adaptation to chemical stress: clues from comparative transcriptomics in Saccharomyces cerevisiae and Candida glabrata, Genome Biol, vol.9, p.164, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00406190

A. Lucau-danila, G. Lelandais, Z. Kozovska, V. Tanty, T. Delaveau et al., Early expression of yeast genes affected by chemical stress, Mol Cell Biol, vol.25, pp.1860-1868, 2005.

S. Znaidi, K. S. Barker, S. Weber, A. M. Alarco, T. T. Liu et al., Identification of the Candida albicans Cap1p regulon, Eukaryot Cell, vol.8, pp.806-820, 2009.

D. Kuo, K. Licon, S. Bandyopadhyay, R. Chuang, C. Luo et al., Coevolution within a transcriptional network by compensatory trans and cis mutations, Genome Res, vol.20, pp.1672-1678, 2010.

D. T. Nguyen, A. M. Alarco, and M. Raymond, Multiple Yap1p-binding sites mediate induction of the yeast major facilitator FLR1 gene in response to drugs, oxidants, and alkylating agents, J Biol Chem, vol.276, pp.1138-1145, 2001.

A. Alexeyenko, I. Tamas, and E. Sonnhammer, Automatic clustering of orthologs and inparalogs shared by multiple proteomes, Bioinformatics, vol.22, pp.9-15, 2006.

S. Altschul, T. Madden, A. Schaffer, J. Zhang, Z. Zhang et al., Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Nucleic Acid Research, vol.25, pp.3389-3402, 1997.

R. Aziz, D. Bartels, A. Best, M. Dejongh, V. Vonstein et al., Rapid Annotations using Subsystems Technology, BMC Genomics, vol.9, p.75, 2008.

P. Dehoux, R. Flores, C. Dauga, G. Zhong, and A. Subtil, Multi-genome identification and characterization of chlamydiae-specific type III secretion substrates: the Inc proteins, BMC Genomics, vol.12, p.109, 2011.
URL : https://hal.archives-ouvertes.fr/pasteur-00567996

A. Marchler-bauer, J. Anderson, F. Chitsaz, M. Derbushire, and C. Deweese-scott, CDD : specific functional annotation with the Conserved Domain Database, Nucleic Acid Research, vol.37, pp.205-215, 2008.

M. Remm, C. Storm, and E. Sonnhammer, Automatic Clustering of Orthologs and In-paralogs from Pairwise Species Comparisons, Journal of Molecular Biology, vol.314, pp.1041-1052, 2001.

F. L. Thompson, T. Iida, and J. Swings, Biodiversity of vibrios. Microbiol Mol Biol Rev, vol.68, issue.3, pp.403-434, 2004.

R. Dryselius, K. Kurokawa, and T. Iida, Vibrionaceae, a versatile bacterial family with evolutionarily conserved variability, Res Microbiol, vol.158, issue.6, pp.479-86, 2007.

D. Mazel, Integrons: agents of bacterial evolution, Nat Rev Microbiol, vol.4, issue.8, pp.608-628, 2006.

F. J. Reen, S. Almagro-moreno, D. Ussery, and E. F. Boyd, The genomic code: inferring Vibrionaceae niche specialization, Nat Rev Microbiol, vol.4, issue.9, pp.697-704, 2006.

T. Vesth, T. M. Wassenar, P. F. Hallin, L. Snipen, K. Lagesen et al., On the origins of a Vibrio species, Microb Ecol, vol.59, issue.1, pp.1-13, 2010.

B. Austin, Vibrios as causal agents of zoonoses, Vet Microbiol, vol.140, issue.3-4, pp.310-317, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00556049

F. , L. Roux, and B. Austin, Vibrio splendidus, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00458183

S. Bentley, Sequencing the species pan-genome, Nat Rev Microbiol, vol.7, issue.4, pp.258-267, 2009.

D. J. Grimes, C. N. Johnson, K. S. Dillon, A. R. Flowers, N. F. Noriea et al., What genomic sequence information has revealed about Vibrio ecology in the ocean--a review, Microb Ecol, vol.58, issue.3, pp.447-60, 2009.

C. C. Thompson, A. C. Vicente, R. C. Souza, A. T. Vasconcelos, T. Vesth et al., Genomic taxonomy of Vibrios, vol.9, p.258, 2009.

P. Romby, F. Vandenesch, and E. G. Wagner, The role of RNAs in the regulation of virulence-gene expression, Curr Opin Microbiol, vol.9, issue.2, pp.229-265, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00094433

J. M. Liu, J. Livny, M. S. Lawrence, M. D. Kimball, M. Waldor et al., Experimental discovery of sRNAs in Vibrio cholerae by direct cloning, 5S/tRNA depletion and parallel sequencing, Nucleic Acids Res, vol.37, issue.6, p.46, 2009.

F. Le-roux, J. Binesse, D. Saulnier, and D. Mazel, Construction of a Vibrio splendidus mutant lacking the metalloprotease gene vsm by use of a novel counterselectable suicide vector, Appl Environ Microbiol, vol.73, issue.3, pp.777-84, 2007.

F. L. Roux, B. M. Davis, and M. K. Waldor, Conserved small RNAs govern replication and incompatibility of a diverse new plasmid family from marine bacteria, Nucleic Acids Res, vol.39, issue.3, pp.1004-1017, 2011.

D. R. Cook and R. Varshney, From genome studies to agricultural biotechnology: closing the gap between basic plant science and applied agriculture, Current Opinion in Plant Biology, vol.13, pp.115-118, 2010.

B. L. Cantarel, I. Korf, S. M. Robb, G. Parra, E. Ross et al., MAKER: An easy-to-use annotation pipeline designed for emerging model organism genomes, Genome Research, vol.18, pp.188-196, 2008.

C. G. Elsik, K. C. Worley, L. Zhang, N. V. Milshina, H. Jiang et al., Community annotation: Procedures, protocols, and supporting tools, vol.16, pp.1329-1333, 2006.

, Generic Model Organism Database

, The Perl Programming Language

, Catalyst

, Sybase

. Postgresql,

, The Template Toolkit is a fast, flexible and highly extensible template processing system

, The Write Less, Do More, JavaScript Library

W. J. Kent, BLAT-the BLAST-like alignment tool, Genome research, vol.12, issue.4, pp.656-664, 2002.

O. Madani and M. Connor, Large-scale many-class learning, SIAM Conf. on Data Mining (SDM), 2008.

R. Saidi, M. Maddouri, and E. M. Nguifo, Protein sequences classification by means of feature extraction with substitution matrices, BMC Bioinformatics, vol.11, p.175, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00459421

S. Mitra, P. Rupek, D. C. Richter, T. Urich, J. A. Gilbert et al., Functional analysis of metagenomes and metatranscriptomes using SEED and KEGG, BMC Bioinformatics, vol.12, issue.1, p.21, 2011.

L. S. Johnson, S. R. Eddy, and E. Portugaly, Hidden Markov model speed heuristic and iterative HMM search procedure, BMC Bioinformatics, vol.11, p.431, 2010.

V. Boeva, A. Zinovyev, K. Bleakley, J. P. Vert, I. Janoueix-lerosey et al., Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization, Bioinformatics, vol.27, issue.2, pp.268-277, 2011.

B. Zeitouni, V. Boeva, I. Janoueix-lerosey, S. Loeillet, P. Legoix-né et al., SVDetect: a tool to identify genomic structural variations from paired-end and mate-pair sequencing data, Bioinformatics, vol.26, pp.1895-1896, 2010.
URL : https://hal.archives-ouvertes.fr/inserm-00508372

D. Vallenet, S. Engelen, D. Mornico, S. Cruveiller, L. Fleury et al., MicroScope: a platform for microbial genome annotation and comparative genomics, Database, p.21, 2009.

E. Giraud, L. Moulin, D. Vallenet, V. Barbe, E. Cytryn et al., Legumes symbioses: absence of Nod genes in photosynthetic bradyrhizobia, Science, vol.316, pp.1307-1312, 2007.
URL : https://hal.archives-ouvertes.fr/halsde-00151340

C. Rusniok, D. Vallenet, S. Floquet, H. Ewles, C. Mouzé-soulama et al., NeMeSys: a biological resource for narrowing the gap between sequence and function in the human pathogen Neisseria meningitidis, Genome Biology, vol.10, p.110, 2009.
URL : https://hal.archives-ouvertes.fr/pasteur-00663857

F. Ozsolak and P. M. Milos, RNA sequencing: advances, challenges and opportunities, Nature Reviews. Genetics, vol.12, pp.87-98, 2011.

Z. Ning, A. J. Cox, and J. C. Mullikin, SSAHA: a fast search method for large DNA databases, Genome Research, vol.11, pp.1725-1729, 2001.

S. Anders and W. Huber, Differential expression analysis for sequence count data, Genome Biology, vol.11, p.106, 2010.

J. T. Robinson, H. Thorvaldsdóttir, W. Winckler, M. Guttman, E. S. Lander et al., Integrative genomics viewer, Nature Biotechnology, vol.29, pp.24-26, 2011.

A. I. Saeed, V. Sharov, J. White, J. Li, W. Liang et al., TM4: a free, open-source system for microarray data management and analysis, BioTechniques, vol.34, pp.374-378, 2003.

V. De-berardinis, M. Durot, J. Weissenbach, and M. Salanoubat, Acinetobacter baylyi ADP1 as a model for metabolic system biology, Current Opinion in Microbiology, vol.12, pp.568-576, 2009.

J. Li, H. Jiang, and W. H. Wong, Modeling non-uniformity in short-read rates in RNA-Seq data, Genome Biology, vol.11, p.50, 2010.

L. Rueda and L. Qin, A new method for DNA microarray image segmentation. Image Analysis and Recognition, pp.886-893, 2005.

N. Giannakeas, P. S. Karvelis, and D. I. Fotiadis, A classification-based segmentation of cDNA microarray images using Support Vector machines, Engineering in Medicine and Biology Society, pp.875-878, 2008.

A. Y. Ng, M. I. Jordan, and Y. Weiss, On spectral clustering: analysis and an algorithm, NIPS, pp.849-856, 2002.

E. Yom-tov and N. Slonim, Parallel pairwise clustering SIAM Int. Conf. on Data Mining, 2009.

W. Chen, S. Yangqiu, H. Bai, C. Lin, and E. Y. Chang, Parallel Spectral Clustering in Distributed Systems. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010.

S. Mouysset, J. Noailles, and D. Ruiz, Using a Global Parameter for Gaussian Affinity Matrices in Spectral Clustering, High Performance Computing for Computational Science-VECPAR, pp.378-390, 2008.

M. Schena, D. Shalon, R. W. Davis, and P. O. Brown, Quantitative monitoring of gene expression patterns with acomplementary DNA microarray, Science, vol.270, pp.467-470, 1995.

T. Sorlie, C. M. Perou, R. Tibshirani, T. Aas, S. Geisler et al., Eystein Lonning and A.L. Borresen-Dale, Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications, Proc Natl Acad Sci U S A, vol.98, pp.10869-10874, 2001.

C. Sotiriou, P. Wirapati, S. Loi, A. Harris, S. Fox et al., Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis, J Natl Cancer Inst, vol.98, pp.262-272, 2006.

H. Liu, I. Bebu, and X. Li, Microarray probes and probe sets, Front Biosci, vol.2, pp.325-338, 2010.

S. Imbeaud and C. Auffray, The 39 steps' in gene expression profiling: critical issues and proposed best practices for microarray experiments, Drug Discov Today, vol.10, pp.1175-1182, 2005.

L. Gautier, M. Moller, L. Friis-hansen, and S. Knudsen, Alternative mapping of probes to genes for Affymetrix chips, BMC Bioinformatics, vol.5, p.111, 2004.

M. Dai, P. Wang, A. D. Boyd, G. Kostov, B. Athey et al., Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data, Nucleic Acids Res, vol.33, p.175, 2005.

J. Harbig, R. Sprinkle, and S. A. Enkemann, A sequence-based identification of the genes detected by probesets on the Affymetrix U133 plus 2.0 array, Nucleic Acids Res, vol.33, p.31, 2005.

H. Liu, B. R. Zeeberg, G. Qu, A. G. Koru, A. Ferrucci et al., AffyProbeMiner: a web resource for computing or retrieving accurately redefined Affymetrix probe sets, Bioinformatics, vol.23, pp.2385-2390, 2007.

B. Ballester, N. Johnson, G. Proctor, and P. Flicek, Consistent annotation of gene expression arrays, BMC Genomics, vol.11, p.294, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01615157

M. Garcia, Linking interactome to disease: a network-based analysis of metastatic relapse in breast cancer, Handbook of Research on Computational and Systems Biology: Interdisciplinary Applications. IGI Global, pp.406-427, 2011.

H. Y. Chuang, Network-based classification of breast cancer metastasis, Mol Syst Biol, vol.3, p.140, 2007.

T. S. Prasad, Human protein reference database-2009 update, Nucleic Acids Res, vol.37, pp.767-772, 2009.

A. K. Ramani, Consolidating the set of known human protein-protein interactions in preparation for large-scale mapping of the human interactome, Genome Biol, vol.6, issue.5, p.40, 2005.

A. , Mint, the molecular interaction database: 2009 update, Nucleic Acids Res, vol.38, pp.532-539, 2010.

B. Aranda, The intact molecular interaction database in 2010, Nucleic Acids Res, vol.38, pp.525-531, 2010.

L. Salwinski, The database of interacting proteins: 2004 update, Nucleic Acids Res, vol.32, pp.449-451, 2004.

C. Desmedt, Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes, Clin Cancer Res, vol.14, issue.16, pp.5158-5165, 2008.

S. Loi, Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen, BMC Genomics, vol.9, p.239, 2008.

R. Sabatier, A gene expression signature identifies two prognostic subgroups of basal breast cancer, Breast Cancer Res Treat, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00583558

M. Schmidt, The humoral immune system has a key prognostic impact in node-negative breast cancer, Cancer Res, vol.68, issue.13, pp.5405-5413, 2008.

Y. Wang, Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer, Lancet, vol.365, issue.9460, pp.671-679, 2005.

S. F. Altschul, W. Gish, W. Miller, E. W. Myers, and D. J. Lipman, Basic local alignment search tool, J Mol Biol, vol.215, issue.3, pp.403-410, 1990.

L. Noe and G. Kucherov, YASS: enhancing the sensitivity of DNA similarity search, Nucleic Acids Res, vol.33, issue.2, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00100004

P. P. Gardner, J. Daub, J. G. Tate, E. P. Nawrocki, D. L. Kolbe et al., Rfam: updates to the RNA families database, Nucleic Acids Res, vol.37, 2009.

T. Kin, K. Yamada, G. Terai, H. Okida, Y. Yoshinari et al., fRNAdb: a platform for mining/annotating functional RNA candidates from non-coding RNA sequences, Nucleic Acids Res, vol.35, 2007.

S. Griffiths-jones, H. K. Saini, S. Van-dongen, and A. J. Enright, miRBase: tools for microRNA genomics, Nucleic Acids Res, vol.36, 2008.

E. P. Nawrocki, D. L. Kolbe, and S. R. Eddy, Infernal 1.0: Inference of RNA alignments, Bioinformatics, vol.25, issue.10, 2009.

M. Zytnicki, C. Gaspin, and T. Schiex, DARN! A Weighted Constraint Solver for RNA Motif Localization, Constraints, vol.13, 2008.

D. Gautheret and A. Lambert, Direct RNA Motif Definition and Identification from Multiple Sequence Alignments using Secondary Structure Profiles, J Mol Biol, vol.313, pp.1003-1014, 2001.

K. Lagesen, P. Hallin, E. A. Rødland, H. Staerfeldt, T. Rognes et al., RNAmmer: consistent and rapid annotation of ribosomal RNA genes, Nucleic Acids Res, vol.35, issue.9, 2003.

T. M. Lowe and S. R. Eddy, tRNAscan-SE: A program for improved detection of transfer RNA genes in genomic sequence, Nucleic Acids Res, vol.25, issue.5, 1997.

B. Grenier-boley, A. De-monte, and H. Touzet, CG-seq: a toolbox for automatic annotation of genomes by comparative analysis, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00530507

H. Touzet and O. Perriquet, CARNAC: folding families of non coding RNAs, Nucleic Acids Res, vol.142, 2004.

S. Washietl, I. L. Hofacker, and P. F. Stadler, Fast and reliable prediction of noncoding RNAs, Proc. Natl. Acad. Sci. U.S.A, vol.102, pp.2454-2459, 2005.

K. D. Taganov, M. P. Boldin, K. J. Chang, and D. Baltimore, NF-?B-dependent induction of microRNA miR-146, an inhibitor targeted to signaling proteins of innate immune responses, Proc Natl Acad Sci, vol.103, issue.33, pp.12481-12486, 2006.

L. Navarro, P. Dunoyer, F. Jay, B. Arnold, N. Dharmasiri et al., A plant miRNA contributes to antibacterial resistance by repressing auxin signalling, Science, issue.5772, pp.436-445, 2006.

L. Navarro, F. Jay, K. Nomura, S. Y. He, and O. Voinnet, Suppression of the microRNA pathway by bacterial effector proteins, Science, vol.321, pp.964-967, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00339296

F. Jay, J. Renou, O. Voinnet, and L. Navarro, Biotic stress-associated microRNAs : Identification, detection, regulation and functional analyses, Methods in Molecular Biology, vol.592, pp.183-202, 2009.

S. Katiyar-agarwal and H. Jin, Role of small RNAs in host-microbe interactions, Annu. Rev. Phytopathol, vol.48, pp.225-271, 2010.

M. A. Matzke and J. A. Birchler, RNAi-mediated pathways in the nucleus, Nat. Rev. Genet, vol.6, issue.1, pp.24-35, 2005.

N. Fahlgren, C. M. Sullivan, K. D. Kasschau, E. J. Chapman, J. S. Cumbie et al., Computational and analytical framework for small RNA profiling by high-throughput sequencing, RNA, vol.15, issue.5, pp.992-1002, 2009.

P. Kapranov, A. T. Willingham, and T. R. Gingeras, Genome-wide transcription and the implications for genomic organization, Nat Rev Genet, vol.8, pp.413-436, 2007.

, International Human Genome Sequencing Consortium, Initial sequencing and analysis of the human genome, Nature, vol.409, pp.860-921, 2001.

M. G. Kidwell and D. R. Lisch, Perspective: transposable elements and host genome evolution, Trends Ecol. Evol, vol.15, pp.95-99, 2001.

N. L. Craig, R. Gragie, M. Gellert, and A. M. Lambowitz, Mobile DNA II Second Edition, 2002.

T. Wicker, F. Sabot, A. Hua-van, J. L. Bennetzen, P. Capy et al., A unified classification system for eukaryotic transposable elements, Nat Rev Genet, vol.8, pp.973-82, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00169819

S. R. Wessler, T. E. Bureau, and S. E. White, LTR-retrotransposons and MITEs: important players in the evolution of plant genomes, Genet. Dev, vol.5, pp.814-821, 1995.

C. Feschotte and C. Mouches, Evidence that a family of miniature inverted-repeat transposable elements (MITEs) from the Arabidopsis thaliana genome has arisen from a pogo-like DNA transposon, Mol. Biol. Evol, vol.17, pp.4051-730, 2000.

H. Kawagoe-takaki, N. Nameki, M. Kajikawa, and N. Okada, Probing the secondary structure of salmon SmaI SINE RNA, Gene, vol.365, pp.67-73, 2006.

J. D. Suntera, S. P. Patela, R. A. Skiltona, N. Githakaa, D. P. Knowlesb et al., A novel SINE family occurs frequently in both genomic DNA and transcribed sequences in ixodid ticks of the arthropod sub-phylum Chelicerata, Genet. Dev, vol.415, pp.13-22, 2008.

Y. Chen, F. Zhou, G. Li, and Y. Xu, A recently active miniature inverted-repeat transposable element, Chunjie, inserted into an operon without disturbing the operon structure in Geobacter uraniireducens Rf4, Genetics, vol.179, pp.2291-2298, 2008.

H. Kuang, C. Padmanabhan, F. Li, A. Kamei, P. B. Bhaskar et al., Identification of miniature inverted-repeat transposable elements (MITEs) and biogenesis of their siRNAs in the Solanaceae: New functional implications for MITEs, Genome Res, vol.19, pp.42-56, 2008.

G. J. Hannon and J. J. Rossi, Unlocking the potential of the human genome with RNA interference, Nature, vol.431, pp.371-378, 2004.

R. Rana, Illuminating the silence: understanding the structure and function of small RNAs, Molecular Cell Biology, vol.8, pp.23-36, 2007.

D. Bartel, MicroRNAs: genomics, biogenesis, mechanism and function, Cell, vol.116, pp.281-197, 2004.

L. He and G. Hannon, microRNAs: small RNAs with a big role in gene regulation, Nat. Rev. Genet, vol.5, pp.522-531, 2004.

Y. Lee, M. Kim, J. Han, K. Yeom, K. S. Lee et al., microRNA genes are transcribed by RNA polymerase II, EMBO J, vol.23, pp.4051-4060, 2004.

J. Piriyapongsa and I. K. Jordan, Dual coding of siRNAs and miRNAs by plant transposable element, RNA, vol.14, pp.814-821, 2008.

J. Piriyapongsa and I. K. Jordan, A Family of Human MicroRNA Genes from Miniature Inverted-Repeat Transposable Elements, PLoS ONE, vol.2, p.203, 2007.

N. R. Smalheiser and V. I. Torvik, Mammalian microRNAs derived from genomic repeats, Trends Genet, vol.21, pp.322-326, 2005.

S. Griffiths-jones, H. Saini, S. Van-dongen, and A. Enright, miRBase: tools for microRNA genomics, Nucleic Acids Res, vol.36, pp.154-158, 2008.

J. Piriyapongsa, L. Marino-ramirez, and I. K. Jordan, Origin and Evolution of Human microRNAs From Transposable Elements, Genetics, vol.176, pp.1323-1337, 2007.

E. Berezikov, N. Robine, A. Samsonova, J. O. Westholm, A. Naqvi et al., Deep annotation of Drosophila melanogaster microRNAs yields insights

, Genome Res, vol.21, pp.203-215, 2011.

P. Landgraf, A Mammalian microRNA Expression Atlas Based on Small RNA Library Sequencing, Cell, vol.129, pp.1401-1414, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00159802

A. Sewer, N. Paul, P. Landgraf, A. Aravin, S. Pfeffer et al., Identification of clustered microRNAs using an ab initio prediction method, BMC Bioinformatics, vol.6, p.267, 2005.

J. Jurka, P. Klonowski, V. Dagman, and P. Pelton, CENSOR -a program for identification and elimination of repetitive elements from DNA sequences, Comput Chem, vol.20, pp.119-140, 1996.

T. Flutre, E. Duprat, C. Feuillet, and H. Quesneville, Considering Transposable Element Diversification in De Novo Annotation Approaches, PLoS ONE, vol.6, p.16526, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00956366

W. J. Kent, BLAT -The BLAST-Like Alignment Tool, Genome Research, vol.4, pp.656-664, 2002.

P. A. Fujita, The UCSC Genome Browser database: update 2011, Nucleic Acids Res, vol.39, pp.876-82, 2011.

M. A. Larkin, G. Blackshields, R. Brown, P. A. Chenna, H. Mcgettigan et al., Clustal W and Clustal X version 2.0. Bioinformatics, vol.23, pp.2947-2955, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00206210

J. Jurka, V. V. Kapitonov, A. Pavlicek, P. Klonowski, O. Kohany et al., Repbase Update, a database of eukaryotic repetitive elements, Cytogentic and Genome Research, vol.110, pp.462-467, 2005.

. Bc and . Meyers, Criteria for Annotation of Plant MicroRNAs, The Plant Cell, vol.20, pp.3186-3190, 2008.

Y. Yan, Y. Zhang, K. Yang, Z. Sun, Y. Fu et al., Small RNAs from MITE-derived stem-loop precursors regulate abscisic acid signaling and abiotic stress responses in rice, The Plant Journal, vol.65, pp.820-828, 2011.

H. J. Dyson and P. E. Wright, Intrinsically unstructured proteins and their functions, Nat Rev Mol Cell Biol, vol.6, issue.3, pp.197-208, 2005.

J. Bellay, S. Han, M. Michaut, T. Kim, M. Costanzo et al., Bringing order to protein disorder through comparative genomics and genetic interactions, Genome Biol, vol.12, issue.2, p.14, 2011.

L. M. Iakoucheva, P. Radivojac, C. J. Brown, T. R. O'connor, J. G. Sikes et al., The importance of intrinsic disorder for protein phosphorylation, Nucleic Acids Res, vol.32, issue.3, pp.1037-1049, 2004.

I. Bozic, T. Antal, H. Ohtsuki, H. Carter, D. Kim et al., Kinzler et al, Accumulation of driver and passenger mutations during tumor progression, Proc Natl Acad Sci, vol.107, issue.43, pp.18545-18550, 2010.

J. L. Jestin and A. Kempf, Chain termination codons and polymerase-induced frameshift mutations, FEBS Lett, vol.419, pp.153-156, 1997.

J. L. Jestin, Degeneracy in the genetic code and its symmetries by base substitutions, Comp. Rend. Biol, vol.329, pp.168-171, 2006.

J. L. Jestin and C. Soulé, Symmetries by base substitutions in the genetic code predict 2' or 3' aminoacylation of tRNAs, J. Theor. Biol, vol.247, pp.391-394, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00139647

Y. B. Rumer, About the codon's systematization in the genetic code, Proc. Acad. Sci. USSR, vol.167, pp.1393-1394, 1966.

A. M. Phillippy, K. Ayanbule, N. J. Edwards, and S. L. Salzberg, Insignia: a DNA signature search web server for diagnostic assay development, Nucleic Acids Res, vol.37, pp.229-234, 2009.

J. Kent, UCSC In silico PCR

S. F. Altschul, W. Gish, W. Miller, E. W. Myers, and D. J. Lipman, Basic local alignment search tool, Jmol. Biol, vol.215, issue.3, pp.403-410, 1990.

S. Rozen and H. J. Skaletsky, Primer3 on the WWW for general users and for biologist programmers, Bioinformatics Methods and Protocols: Methods in Molecular Biology, pp.365-386, 2000.

P. Rice, I. Longden, and A. Bleasby, EMBOSS: The European Molecular Biology Open Software Suite, Trends in Genetics, vol.16, issue.6, pp.276-277, 2000.

E. Sayers and D. Wheeler, Building Customized Data Pipelines Using the Entrez Programming Utilities (eUtils, NCBI eUtils

A. Chao, R. K. Colwell, C. Lin, and N. J. Gotelli, Sufficient sampling for asymptotic minimum species richness estimators, Ecology, vol.90, issue.4, pp.1125-1133, 2009.

I. Uchiyama, T. Higuchi, and M. Kawai, MBGD update 2010: toward a comprehensive resource for exploring microbial genome diversity, Nucl. Acids Res, vol.38, pp.361-365, 2010.

M. Z. Ansari, G. Yadav, R. S. Gokhale, and D. Mohanty, NRPS-PKS: a knowledge-based resource for analysis of NRPS/PKS megasynthetase, Nucl. Acids Res, vol.32, pp.405-413, 2004.

B. O. Bachmann and J. Ravel, In Silico Prediction of Microbial Secondary Metabolic Pathways from DNA Sequence Data, Meth. Enzymol, vol.458, pp.181-217, 2009.

C. Rausch, T. Weber, O. Kohlbacher, W. Wohlleben, and D. H. Huson, Specificity prediction of adenylation domains in nonribosomal peptide synthetases (NRPS) using Transductive Support Vector Machines (TSVM)

, Nucl. Acids Res, vol.33, pp.5799-5808, 2005.

S. Caboche, M. Pupin, V. Leclère, A. Fontaine, P. Jacques et al., NORINE: a database of nonribosomal peptides, Nucl. Acids Res, vol.36, pp.326-331, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00281012

S. Caboche, M. Pupin, V. Leclère, P. Jacques, and G. Kucherov, Structural pattern matching of nonribosomal peptides, BMC Structural Biology, vol.9, p.15, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00641486

B. Offmann, M. Tyagi, and A. G. De-brevern, Local Protein Structures. Current Bioinformatics, vol.2, pp.165-202, 2007.

C. Benros, A. G. De-brevern, C. Etchebest, and S. Hazout, Assessing a novel approach for predicting local 3D protein structures from sequence, Proteins, vol.62, pp.865-880, 2006.
URL : https://hal.archives-ouvertes.fr/inserm-00133180

A. Bornot, C. Etchebest, and A. G. De-brevern, A new prediction strategy for long local protein structures using an original description, Proteins, vol.76, pp.570-587, 2009.
URL : https://hal.archives-ouvertes.fr/inserm-00348740

A. Bornot, C. Etchebest, and A. G. De-brevern, Predicting Protein Flexibility through the Prediction of Local Structures, Proteins, vol.79, pp.839-852, 2011.
URL : https://hal.archives-ouvertes.fr/inserm-00568171

A. G. De-brevern, C. Etchebest, and S. Hazout, Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks, Proteins, vol.41, pp.271-287, 2000.
URL : https://hal.archives-ouvertes.fr/inserm-00132821

A. P. Joseph, A short survey on protein blocks, Biophys Rev, vol.2, pp.137-145, 2010.
URL : https://hal.archives-ouvertes.fr/inserm-00512823

M. Tyagi, A. G. De-brevern, N. Srinivasan, and B. Offmann, Protein structure mining using a structural alphabet, Proteins, vol.71, pp.920-937, 2008.
URL : https://hal.archives-ouvertes.fr/inserm-00176443

A. P. Joseph, N. Srinivasan, and A. G. De-brevern, Improvement of protein structure comparison using a structural alphabet, Biochimie, 2011.
URL : https://hal.archives-ouvertes.fr/inserm-00646245

X. Huang and W. Miller, A time-efficient linear-space local similarity algorithm, Advances in Applied Mathematics, vol.12, pp.337-357, 1991.

J. Gelly, A. P. Joseph, N. Srinivasan, and A. G. De-brevern, iPBA : A tool for protein structure comparison using sequence alignment strategies, Nucleic Acid Research, 2011.
URL : https://hal.archives-ouvertes.fr/inserm-00646241

. Ch, V. Tai, J. F. Sam, J. Gibrat, P. J. Garnier et al., Protein domain assignment from the recurrence of locally similar structures, PROTEINS: Structure, Function, and Bioinformatics, vol.79, pp.853-866, 2011.

. Jf, T. Gibrat, S. H. Madej, and . Bryant, Surprising similarities in structure comparison, Curr Opin Struct Biol, vol.6, issue.3, pp.377-385, 1996.

T. Madej, J. F. Gibrat, and S. H. Bryant, Threading a database of protein cores, Proteins, vol.23, issue.3, pp.356-369, 1995.
URL : https://hal.archives-ouvertes.fr/hal-02701019

V. Sam, C. H. Tai, J. Garnier, J. F. Gibrat, B. Lee et al., ROC and confusion analysis of structure comparison methods identify the main causes of divergence from manual protein classification, BMC bioinformatics, vol.7, p.206, 2006.
URL : https://hal.archives-ouvertes.fr/hal-02663569

J. Martin, G. Letellier, A. Marin, J. F. Taly, A. De-brevern et al., Protein secondary structure assignment revisited: a detailed analysis of different assignment methods, BMC Struct Biol, vol.5, p.17, 2005.
URL : https://hal.archives-ouvertes.fr/inserm-00090199

V. Jallu, V. , M. Dusseaux, S. Panzer, M. F. Torchet et al., ?IIb/?3 integrin: new allelic variants in Glanzmann Thrombasthenia, effects on ITGA2B and ITGB3 mRNA splicing, expression and structure-function, Hum. Mutat, vol.31, pp.237-246, 2010.

V. Jallu, P. Poulain, C. Kaplan, and A. G. De-brevern, 3D protein structure modeling: A tool to provide insight into the platelet alloimmune response, Transfusion Today, 2011.

C. Sanders and J. K. Myers, Disease-related misassembly of membrane proteins, Annu. Rev. Biophys. Biomol. Struct, vol.33, pp.25-51, 2004.

Y. Arinaminpathy, E. Khurana, D. M. Engelman, and M. B. Gerstein, Computations analysis of membrane proteins: the largest class of drug targets, Drug Discov. Today, vol.14, pp.1330-1335, 2009.

A. Elofsson and G. Von-heijne, Membrane Protein Structure: Prediction versus Reality, Annu. Rev. Biochem, vol.76, pp.125-140, 2007.

A. Marsico, A. Henschel, C. Winter, A. Tuukkanen, B. Vassilev et al., Structural fragment clustering reveals novel structural and functional motifs in ?-helical transmembrane proteins, Bmc Bioinformatics, vol.11, p.204, 2010.

A. G. De-brevern and S. Hazout, Hybrid Protein Model (HPM): a method to compact protein 3D-structures information and physicochemical properties, vol.1, pp.49-54, 2000.
URL : https://hal.archives-ouvertes.fr/inserm-00132863

A. G. De-brevern and S. Hazout, Hybrid Protein Model' for optimally defining 3D protein structure fragments, Bioinformatics, vol.19, pp.345-353, 2003.
URL : https://hal.archives-ouvertes.fr/inserm-00133632

Q. Guo, Y. Shen, Y. S. Lee, C. S. Gibbs, M. Mrksich et al., Structural basis for the interaction of Bordetella pertussis adenylyl cyclase toxin with calmodulin, Embo J, vol.24, pp.3190-3201, 2005.

E. Laine, J. D. Yoneda, A. Blondel, and T. E. Malliavin, The conformational plasticity of calmodulin upon calcium complexation gives a model of its interaction with the oedema factor of Bacillus anthracis, Proteins, vol.71, pp.1813-1829, 2008.

J. Srinivasan, T. Cheatham, J. Cieplak, P. Kollman, and D. Case, Continuum solvent studies of the stability of DNA, RNA, and phosphoramidate-DNA helices, J.Am.Chem.Soc, vol.120, pp.9401-9409, 1998.

E. Laine, A. Blondel, and T. E. Malliavin, Dynamics and energetics : a consensus analysis of the impacf of calcium on EF-CaM protein complex, Biophys J, vol.96, issue.4, pp.1249-63, 2009.

J. C. Karst, A. C. Pérez, J. I. Guijarro, B. Raynal, A. Chenal et al., Calmodulin-induced conformational and hydrodynamic changes in the catalytic domain of Bordetella pertussis adenylate cyclase toxin, Biochemistry, vol.49, issue.2, pp.318-346, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00512114

E. Selwa, E. Laine, and T. , Malliavin Affiche, vol.134

Y. Kitamura, A. Ebihara, Y. Agari, A. Shinkai, K. Hirotsu et al., Structure of D-alanine-D-alanine ligase from Thermus thermophilus HB8: cumulative conformational change and enzyme-ligand interactions, Acta Cryst, vol.65, pp.1098-1106, 2009.

D. I. Roper, T. Huyton, A. Vagin, and G. Dodson, The molecular basis of vancomycin resistance in clinically relevant Enterococci: Crystal structure of D-alanyl-D-lactate ligase (VanA), Proc. Natl. Acad. Sci. USA, vol.97, issue.16, pp.8921-8925, 2000.

N. Unwin, Refined structure of the nicotinic acetylcholine receptor at 4Å resolution, J Mol Biol, vol.346, issue.4, pp.967-89, 2005.

P. Taylor, T. T. Talley, Z. Radic, S. B. Hansen, R. E. Hibbs et al., Structure-guided drug design: conferring selectivity among neuronal nicotinic receptor and acetylcholine-binding protein subtypes, Biochemical Pharmacology, vol.74, pp.1164-1171, 2007.

A. Kahraman, R. J. Morris, R. A. Laskowski, and J. M. Thornton, Shape variation in protein binding pockets and their ligands, J Mol Biol, vol.368, pp.283-301, 2007.

P. Guntert, Automated NMR structure calculation with CYANA, Methods Mol Biol, vol.278, pp.353-378, 2004.

W. Rieping, M. Habeck, B. Bardiaux, A. Bernard, T. E. Malliavin et al., ARIA2: automated NOE assignment and data integration in NMR structure calculation, Bioinformatics, vol.23, pp.381-382, 2006.

A. Bernard, F. W. Vranken, B. Bardiaux, M. Nilges, and T. E. Malliavin, Bayesian estimation of NMR restraint potential and weight: A validation on a representative set of protein structures, Proteins, vol.79, issue.5, pp.1525-1537, 2011.

M. Nilges, A. Bernard, B. Bardiaux, T. Malliavin, M. Habeck et al., Accurate NMR structures through minimisation of an extended hybrid energy, Structure, vol.16, issue.9, pp.1305-1317, 2008.

I. W. Davis, A. Leaver-fay, V. B. Chen, J. N. Block, G. J. Kapral et al., MolProbity: all-atom contacts and structure validation for proteins and nucleic acids, Nucleic Acids Research, vol.35, pp.375-383, 2007.

A. Brunger, P. D. Adams, G. M. Clore, W. L. Delano, P. Gros et al., Crystallography & NMR system: A new software suite for macromolecular structure determination, vol.54, pp.905-921, 1998.

C. Blanchet, R. Mollon, D. Thain, and G. Deleage, Grid deployment of legacy bioinformatics applications with transparent data access, 7th IEEE/ACM International Conference on Grid Computing, pp.120-127, 2006.

A. Rosato, A. Bagaria, D. Baker, B. Bardiaux, A. Cavalli et al., CASD-NMR: critical assessment of automated structure determination by NMR, Nature Methods, vol.6, pp.625-626, 2009.

H. Bloemendal, W. Jong, R. Jaenicke, N. H. Lubsen, C. Slingsby et al., Ageing and vision: structure, stability and function of lens crystallins, Prog. Biophys. Mol. Biol, vol.86, pp.407-485, 2004.
URL : https://hal.archives-ouvertes.fr/hal-00085922

G. Kappé, A. G. Purkiss, S. T. Van-genesen, C. Slingsby, and N. H. Lubsen, Explosive expansion of ??-crystallin genes in the ancestral vertebrate, J. Mol. Evol, vol.71, pp.219-230, 2010.

P. Aravind, A. Mishra, S. K. Suman, M. K. Jobby, R. Sankaranarayanan et al., The ??-crystallin superfamily contains a universal motif for binding calcium, Biochemistry, vol.48, pp.12180-12190, 2009.

S. R. Eddy, Profile hidden Markov models, Bioinformatics, vol.14, pp.755-763, 1998.

S. Guindon and O. Gascuel, A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood, Syst. Biol, vol.52, pp.696-704, 2003.

E. Duprat, M. Lefranc, and O. Gascuel, A simple method to predict protein-binding from aligned sequencesapplication to MHC superfamily and beta2-microglobulin, Bioinformatics, vol.22, pp.453-459, 2006.

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

, The CCP4 Suite: Programs for Protein Crystallography, Acta Cryst, vol.50, pp.760-763, 1994.

S. J. Hubbard and J. M. Thornton, , 1993.

M. Jambon, A. Imberty, G. Deléage, and C. Geourjon, A new bioinformatics approach to detect Common 3D Sites in Protein Structures, Protein Structure Function and Genetics, vol.52, pp.137-145, 2003.

O. Doppelt-azeroual, F. Delfaud, F. Moriaud, and A. G. De-brevern, Classification of binding sites with MED-SuMo Multi approach: an application on Purinome, Protein Science, vol.19, issue.4, pp.847-67, 2010.

O. Doppelt-azeroual, F. Moriaud, F. Delfaud, and A. G. De-brevern, Analysis of HSP90 related folds with MED-SuMo classification approach. Drug Design, Development and Therapy, vol.3, pp.59-72, 2009.
URL : https://hal.archives-ouvertes.fr/inserm-00348737

J. Martin, G. Letellier, A. Marin, J. F. Taly, A. G. De-brevern et al., Protein secondary structure assignment revisited: a detailed analysis of different assignment methods, BMC Struct. Biol, vol.5, p.17, 2005.
URL : https://hal.archives-ouvertes.fr/inserm-00090199

L. R. Dodd, T. D. Boone, and D. N. Theodorou, A concerted rotation algorithm for atomistic Monte Carlo simulation of polymer melts and glasses, Molecular Physics, vol.4, pp.961-996, 1993.

S. Sacquin-mora, A. Carbone, and R. Lavery, Identification of protein interaction partners and protein-protein interaction sites, J Mol Biol, vol.382, issue.5, pp.1276-89, 2008.

H. Hwang, T. Vreven, J. Janin, and Z. Weng, , vol.78, pp.3111-3115, 2010.

B. Thiruv, G. Quon, S. A. Saldanha, and B. Steipe, Nh3D: a reference dataset of non-homologous protein structures, BMC Struct Biol, vol.5, p.12, 2005.

D. W. Ritchie and V. Venkatraman, Ultra-Fast FFT Protein Docking On Graphics Processors, Bioinformatics, vol.26, pp.2398-2405, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00537988

S. B. Qin and H. X. Zhou, Meta-PPISP: a meta web server for protein-protein interaction site prediction, vol.23, pp.3386-3387, 2007.

I. N. Berezovsky, A. Y. Grosberg, and E. N. Trifonov, Closed loops of nearly standard size: common basic element of protein structure, FEBS Letters, vol.466, pp.283-286, 2000.

M. Lamarine, J. P. Mornon, N. Berezovsky, and J. Chomilier, Distribution of tightened end fragments of globular proteins statistically matches that of topohydrophobic positions: towards an efficient punctuation of protein folding?, Cellular and Molecular Life Sciences: CMLS, vol.58, pp.492-498, 2001.

I. N. Berezovsky, V. M. Kirzhner, A. Kirzhner, and E. N. Trifonov, Protein folding: looping from hydrophobic nuclei. Proteins, vol.45, pp.346-350, 2001.

A. Poupon and J. P. Mornon, Populations of hydrophobic amino acids within protein globular domains: identification of conserved "topohydrophobic, positions. Proteins, vol.33, pp.329-342, 1998.

I. N. Berezovsky and E. N. Trifonov, Van der Waals locks: loop-n-lock structure of globular proteins, Journal of Molecular Biology, vol.307, pp.1419-1426, 2001.

I. N. Berezovsky, Discrete structure of van der Waals domains in globular proteins, Protein Engineering, vol.16, pp.161-167, 2003.

J. Janin, R. P. Bahadur, and P. Chakrabarti, Protein-protein interaction and quaternary structure, Quarterly Reviews of Biophysics, vol.41, pp.133-180, 2008.

J. A. Wells and C. L. Mcclendon, Reaching for high-hanging fruit in drug discovery at protein-protein interfaces, Nature, vol.450, pp.1001-1009, 2007.

C. J. Capini, S. M. Bertin-maghit, N. Bessis, P. M. Haumont, E. M. Bernier et al., Active immunization against murine TNFalpha peptides in mice: generation of endogenous antibodies crossreacting with the native cytokine and in vivo protection, Vaccine, vol.22, pp.3144-3153, 2004.

S. M. Bertin-maghit, C. J. Capini, N. Bessis, J. Chomilier, S. Muller et al., Improvement of collagen-induced arthritis by active immunization against murine IL-1beta peptides designed by molecular modeling, Vaccine, vol.23, pp.4228-4235, 2005.

P. Vlieghe, V. Lisowski, J. Martinez, and M. Khrestchatisky, Synthetic therapeutic peptides: science and market, Drug Discovery Today, vol.15, pp.40-56, 2010.

N. London, B. Raveh, D. Movshovitz-attias, and O. Schueler-furman, Can self-inhibitory peptides be derived from the interfaces of globular protein-protein interactions, Proteins, vol.78, pp.3140-3149, 2010.

H. M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat et al., The Protein Data Bank, Nucleic Acids Research, vol.28, pp.235-242, 2000.

E. D. Levy, PiQSi: protein quaternary structure investigation, Structure, vol.15, pp.1364-1367, 1993.

H. Hwang, T. Vreven, J. Janin, and Z. Weng, , vol.78, pp.3111-3114, 2010.

E. Krissinel and K. Henrick, Inference of macromolecular assemblies from crystalline state, Journal of Molecular Biology, vol.372, pp.774-797, 2007.

S. J. De-vries and A. M. Bonvin, How proteins get in touch: interface prediction in the study of biomolecular complexes, Current Protein & Peptide Science, vol.9, pp.394-406, 2008.

C. Alland, F. Moreews, D. Boens, M. Carpentier, S. Chiusa et al., RPBS: a web resource for structural bioinformatics, vol.33, pp.44-49, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00180478

G. Koczyk and I. N. Berezovsky, Domain Hierarchy and closed Loops (DHcL): a server for exploring hierarchy of protein domain structure, Nucleic Acids Research, vol.36, pp.239-245, 2008.

J. Wojcik, J. P. Mornon, and J. Chomilier, New efficient statistical sequence-dependent structure prediction of short to medium-sized protein loops based on an exhaustive loop classification, Journal of Molecular Biology, vol.289, pp.1469-1490, 1999.

B. R. Bacon and R. Britton, Clinical penetrance of hereditary hemochromatosis, The New England Journal of Medicine, vol.358, pp.1533-4406, 2008.

G. Anderson and C. D. Vulpe, Mammalian iron transport, Cellular and Molecular Life Sciences : CMLS, vol.66, pp.1420-9071, 2009.

C. Camaschella and P. Strati, Recent advances in iron metabolism and related disorders. Internal and Emergency Medicine, 1970.

N. C. Andrews, Forging a field : the golden age of iron biology, Blood, vol.112, pp.1528-1548, 2008.

R. R. Crichton, Iron Metabolism : From Molecular Mechanisms to Clinical Consequences, 2009.

S. F. Clark, Iron deficiency anemia : diagnosis and management, Current Opinion in Gastroenterology, vol.25, pp.1531-7056, 2009.

S. Altamura and M. U. Muckenthaler, Iron toxicity in diseases of aging : Alzheimer's disease, Parkinson's disease and atherosclerosis, Journal of Alzheimer's Disease : JAD, vol.16, 2009.

F. Achcar, J. M. Camadro, and D. Mestivier, A Boolean probabilistic model of metabolic adaptation to oxygen in relation to iron homeostasis and oxidative stress, BMC Systems Biology, vol.5, p.51, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00624203

S. Van-dongen, A New Cluster Algorithm for Graphs, 1998.

L. Zinger, E. Coissac, P. Choler, and R. A. Geremia, Assessment of microbial communities by graph partitioning in a study of soil fungi in two Alpine meadows, Applied and Environmental Microbiology, vol.75, pp.1098-5336, 2009.

B. S. Lattimore, S. Van-dongen, M. James, and C. Crabbe, GeneMCL in microarray analysis, Computational Biology and Chemistry, vol.29, pp.1476-9271, 2005.

N. Sohaee and C. V. Forst, Identification of functional modules in a PPI network by bounded diameter clustering, Journal of Bioinformatics and Computational Biology, vol.8, pp.219-7200, 2010.

T. Theodosiou, N. Darzentas, L. Angelis, and C. A. Ouzounis, PuReD-MCL : a graph-based PubMed document clustering methodology, Bioinformatics, vol.24, pp.1367-4811, 2008.

M. Ahdesmäki and K. Strimmer, Feature selection in omics prediction problems using cat scores and false nondiscovery rate control, Ann. Appl. Stat, vol.4, pp.503-519, 2010.

S. Wold, H. Antti, F. Lindgren, and J. Ohman, Orthogonal signal correction of near-infrared spectra, Chemometrics Intell. Lab. Syst, vol.44, pp.175-185, 1998.

H. Hache, H. Lehrach, and R. Herwig, Reverse Engineering of Gene Regulatory Networks: A Comparative Study, EURASIP Journal on Bioinformatics and Systems Biology, 2009.

F. Cw-wrigley and . Békés, Glutenin-protein formation during the continuum from anthesis to processing, Cereal Foods World, vol.44, pp.562-565, 1999.

J. Verdier and R. D. Thompson, Transcriptional regulation of storage protein synthesis during dicotyledon seed filling, Plant Cell Physiol, vol.49, pp.1263-1271, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02658752

I. Rubio-somoza, M. Martinez, Z. Abraham, I. Diaz, and P. Carbonero, Ternary complex formation between HvMYBS3 and other factors involved in transcriptional control in barley seeds, Plant J, vol.47, pp.269-281, 2006.

M. Agier, J. M. Petit, and E. Suzuki, Unifying framework for rule semantics: Application to gene expression data, Fundamenta Informaticae, vol.78, pp.543-559, 2007.
URL : https://hal.archives-ouvertes.fr/hal-01501476

I. Romeuf, Identification in silico des facteurs de transcription du blé tendre (Triticum aestivum) et mise en évidence des facteurs de transcription impliqués dans la synthèse des protéines de réserve, 2010.

H. Wieser, R. Guster, and S. Tucher, Influence of sulphur fertilisation on quantities and proportions of gluten protein types in wheat flour, J. Cereal Sci, vol.40, pp.239-244, 2004.

M. Ashburner, C. A. Ball, J. A. Blake, D. Botstein, H. Butler et al., Gene Ontology: tool for the unification of biology, Nature Genetics, vol.25, pp.25-29, 2000.

V. A. Huynh-thu, A. Irrthum, L. Wehenkel, and P. Geurts, Inferring regulatory networks from expression data using tree-based methods, PLoS ONE, vol.5, issue.9, 2010.

M. S. Cline, M. Smoot, E. Cerami, A. Kuchinsky, N. Landys et al., Integration of biological networks and gene expression data using cytoscape, Nat Protoc, vol.2, issue.10, pp.2366-82, 2007.

T. A. Henzinger, The theory of hybrid automata, 1996.

K. H. Johansson, Hybrid control systems, Sensors & Systems, Royal Institute of Technology, 1044.

M. S. Branicky, Stability of switched and hybrid systems. Decision and Control, Proceedings of the 33rd IEEE Conference on Decision and Control, vol.4, pp.3498-3503, 1994.

R. Shorten, F. Wirth, O. Mason, K. Wulff, . Ch et al., Stability criteria for switched and hybrid systems, SIAM REVIEW, vol.49, pp.545-592, 2005.

L. Tavernini, Differential automata and their discrete simulators, Nonlinear Analysis, vol.11, issue.6, pp.665-683, 1987.

H. Kitano, Computational systems biology, Nature, vol.420, issue.6912, pp.206-210, 2002.

W. Callebaut and D. Rasskin-gutman, Modularity: Understanding the Development and Evolution of Natural Complex Systems, 2005.

J. J. Tyson, Modeling the cell division cycle: cdc2 and cyclin interactions, Proceedings of the National Academy of Sciences of the United States of America, vol.88, issue.16, pp.7328-7332, 1991.

. Ch, M. Li, N. Donizelli, H. Rodriguez, L. Dharuri et al., BioModels database: An enhanced, curated and annotated resource for published quantitative kinetic models, BMC Systems Biology, vol.4, issue.1, p.92, 2010.

A. Arnold, D. Bégay, and P. Crubillé, Construction and analysis of transition systems with MEC, 1994.

L. D. Alfaro, Stochastic transition systems, Proceedings CONCUR, vol.98, pp.423-438, 1998.

J. Gebert, N. Radde, and G. W. Weber, Modeling gene regulatory networks with piecewise linear differential equations, European Journal of Operational Research, vol.181, issue.3, pp.1148-1165, 2007.

D. Schittler, J. Hasenauer, F. Allgöwer, and S. Waldherr, Cell differentiation modeled via a coupled two-switch regulatory networks, Chaos, vol.20, issue.4, 2010.

A. Arnold, G. Point, A. Griffault, and A. Rauzy, The AltaRica formalism for describing concurrent systems, Fundam. Inf, vol.40, issue.2-3, pp.109-124, 1999.

M. Hucka, F. Bergmann, S. Hoops, S. Keating, S. Sahle et al., The Systems Biology Markup Language SBML: Language Specification for Level 3 Version 1 Core Release 1 Candidate, Nature Precedings, 2010.

A. V. Hill, The possible effects of the aggregation of the molecules of haemoglobin on its dissociation curves, J.Physiol, vol.40, pp.iv-vii, 1910.

V. Krishnan, H. U. Bryant, and O. A. Macdougald, Regulation of bone mass by wnt signaling, The Journal of Clinical Investigation, vol.116, issue.5, pp.1202-1209, 2006.

K. Volz, The functional duality of iron regulatory protein 1, Curr Opin Struct Biol, vol.18, pp.106-111, 2008.

C. A. Maxwell, J. Mccarthy, and E. Turley, Cell-surface and mitotic-spindle RHAMM: moonlighting or dual oncogenic functions?, J Cell Sci, vol.121, pp.925-932, 2008.

E. Becker, A. Guénoche, and C. Brun, Systèmes de classes chevauchantes pour la recherche de protéines multifonctionnelles, Actes des Journées Ouvertes Biologie Informatique Mathématiques (JOBIM), pp.49-54, 2009.

, The moonlighting function of pyruvate carboxylase resides in the non-catalytic end of the TIM barrel, Biochim Biophys Acta, vol.1803, pp.1038-1042, 2010.

I. Wapinski, A. Pfeffer, N. Friedman, and A. Regev, Natural history and evolutionary principles of gene duplication in fungi, Nature, vol.6, issue.7158, pp.54-61, 2007.

K. Hanada, C. Zou, K. Lehti-shiu, S. H. Shinozaki, and . Shiu, Importance of lineage-specific expansion of plant tandem duplicates in the adaptive response to environmental stimuli, Plant Physiol, vol.148, issue.2, pp.993-1003, 2008.

G. C. Conant and K. H. Wolfe, Turning a hobby into a job: how duplicated genes find new functions, Nat Rev Genet, vol.9, issue.12, pp.938-50, 2008.

K. Hanada, T. Kuromori, F. Myouga, T. Toyoda, and K. Shinozaki, Increased Expression and Protein Divergence in Duplicate Genes Is Associated with Morphological Diversification, PLoS Genet, vol.5, issue.12, p.1000781, 2009.

R. Zaag, E. Birmelé, and C. Rizzon, Topological characteristics of the functionalisation process for duplicated genes in PPI networks of Arabidopsis thaliana, JOBIM, 2010.

P. Pons and M. Latapy, Computing communities in large networks using random walks, Most, vol.10, issue.2, pp.1-20, 2005.

J. A. Imlay, Cellular defenses against superoxide and hydrogen peroxide, Annu. Rev. Biochem, vol.77, pp.755-776, 2008.

J. M. Mccord and I. Fridovich, Superoxide dismutase. An enzymic function for erythrocuprein (hemocuprein), J. Biol. Chem, vol.244, issue.22, pp.6049-6055, 1969.

I. Moura, P. Tavares, J. J. Moura, N. Ravi, B. H. Huynh et al., Purification and characterization of desulfoferrodoxin. A novel protein from Desulfovibrio desulfuricans (ATCC 27774) and from Desulfovibrio vulgaris (strain Hildenborough) that contains a distorted rubredoxin center and a mononuclear ferrous center, J. Biol. Chem, vol.265, issue.35, pp.21596-21602, 1990.

V. Niviere and M. Fontecave, Discovery of superoxide reductase: an historical perspective, J. Biol. Inorg. Chem, vol.9, issue.2, pp.119-123, 2004.
URL : https://hal.archives-ouvertes.fr/hal-01075793

S. I. Liochev and I. Fridovich, A mechanism for complementation of the sodA sodB defect in Escherichia coli by overproduction of the rbo gene product (desulfoferrodoxin) from Desulfoarculus baarsii, J. Biol. Chem, vol.272, issue.41, pp.25573-25575, 1997.

L. Chen, P. Sharma, J. L. Gall, A. M. Mariano, M. Teixeira et al., A blue non-heme iron protein from Desulfovibrio gigas, Eur. J. Biochem, vol.226, issue.2, pp.613-618, 1994.

F. Rusnak, C. Ascenso, I. Moura, and J. J. Moura, Superoxide reductase activities of neelaredoxin and desulfoferrodoxin metalloproteins, Methods Enzymol, vol.349, pp.243-258, 2002.

A. F. Pinto, J. V. Rodrigues, and M. Teixeira, Reductive elimination of superoxide: Structure and mechanism of superoxide reductases, Biochim. Biophys. Acta, vol.1804, issue.2, pp.285-297, 2010.

D. M. Kurtz and E. D. Coulter, The mechanism(s) of superoxide reduction by superoxide reductases in vitro and in vivo, J. Biol. Inorg. Chem, vol.7, issue.6, pp.653-658, 2002.

S. A. Pereira, P. Tavares, F. Folgosa, R. M. Almeida, I. Moura et al., European Journal of Inorganic Chemistry. European Journal of Inorganic Chemistry, issue.18, pp.2569-2581, 2007.

M. Lombard, D. Touati, M. Fontecave, and V. Niviere, Superoxide reductase as a unique defense system against superoxide stress in the microaerophile Treponema pallidum, J. Biol. Chem, vol.275, issue.35, pp.27021-27026, 2000.
URL : https://hal.archives-ouvertes.fr/hal-01075805

T. Jovanovic, C. Ascenso, K. R. Hazlett, R. Sikkink, C. Krebs et al., Radolf et al: Neelaredoxin, an iron-binding protein from the syphilis spirochete, Treponema pallidum, is a superoxide reductase, J. Biol. Chem, vol.275, issue.37, pp.28439-28448, 2000.

D. Goudenege, S. Avner, C. Lucchetti-miganeh, and F. Barloy-hubler, CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources, BMC Microbiol, vol.10, p.88, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00471841

A. Dolla, M. Fournier, and Z. Dermoun, Oxygen defense in sulfate-reducing bacteria, J. Biotechnol, vol.126, issue.1, pp.87-100, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00475671

F. Rapaport, A. Zinovyev, M. Dutreix, E. Barillot, and J. Vert, Classification of microarray data using gene networks, Bioinformatics, vol.8, issue.35, pp.1-15, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00433577

R. Singh, J. Xu, and B. Berger, Global alignment of multiple protein interaction networks with application to functional orthology detection, Proc Natl Acad Sci U S A, vol.105, issue.35, pp.12763-12771, 2008.

S. Sansone, P. Rocca-serra, M. Brandizi, A. Brazma, D. Field et al., The first RSBI (ISA-TAB) workshop: "can a simple format work for complex studies?, Omics, vol.12, pp.143-149, 2008.

M. Terrasse and M. Roux, Metamodelling architectures for complex data integration in systems biology, In.t J. Biomed. Eng. Technol, vol.3, pp.22-42, 2010.

A. R. Jones, M. Miller, R. Aebersold, R. Apweiler, C. A. Ball et al., The Functional Genomics Experiment model (FuGE): an extensible framework for standards in functional genomics, Nature Biotech, vol.25, pp.1127-1133, 2007.

P. Rocca-serra, M. Brandizi, E. Maguire, N. Sklyar, C. Taylor et al., ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level, Bioinformatics, vol.26, pp.2354-2356, 2010.

E. P. Hoffman, R. H. Brown, J. , and L. M. Kunkel, Dystrophin: the protein product of the Duchenne muscular dystrophy locus, Cell, vol.51, pp.919-928, 1987.

M. Koenig, E. P. Hoffman, C. J. Bertelson, A. P. Monaco, C. Feener et al., Complete cloning of the Duchenne muscular dystrophy (DMD) cDNA and preliminary genomic organization of the DMD gene in normal and affected individuals, Cell, vol.50, pp.509-517, 1987.

E. Le-rumeur, S. J. Winder, and J. F. Hubert, Dystrophin: More than just the sum of its parts, Biochim Biophys Acta, vol.1804, pp.1713-1722, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00592430

A. P. Monaco, C. J. Bertelson, S. Liechti-gallati, H. Moser, and L. M. Kunkel, An explanation for the phenotypic differences between patients bearing partial deletions of the DMD locus, Genomics, vol.2, pp.90-95, 1988.

I. González, S. Déjean, P. Martin, O. Gonçalves, P. Besse et al., Highlighting relationships between heteregeneous biological data through graphical displays based on regularized Canonical Correlation Analysis, Journal of Biological Systems, vol.17, pp.173-199, 2009.

S. Waaijenborg, P. C. Verselewel-de-witt-hamer, and A. Zwinderman, Quantifying the association between gene expressions and dna-markers by penalized canonical correlation analysis, Statistical Applications in Genetics and Molecular Biology, vol.7, issue.1, 2008.

E. Parkhomenko, D. Tritchler, and J. Beyene, Sparse canonical correlation analysis with application to genomic data integration, Statistical Applications in Genetics and Molecular Biology, vol.7, 2009.

K. Cao, P. Martin, C. Robert-granié, and P. Besse, Sparse canonical methods for biological data integration: application to a cross-platform study, BMC Bioinformatics, vol.10, p.34, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00323818

D. M. Witten, R. Tibshirani, and T. Hastie, A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis, Biostatistics, vol.10, pp.515-534, 2009.

K. Cao, D. Rossouw, C. Robert-granié, and P. Besse, A sparse PLS for variable selection when integrating omics data, Statistical Applications in Genetics and Molecular Biology, vol.7, p.29, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00300204

H. Chun and S. Keles, Sparse partial least squares regression for simultaneous dimension reduction and variable selection, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.72, pp.3-25, 2010.

H. D. Vinod, Canonical ridge and econometrics of joint production, Journal of Econometrics, vol.6, pp.129-137, 1976.

I. González, S. Déjean, P. Martin, and A. Baccini, CCA: An R Package to extend Canonical Correlation Analysis, Journal of Statistical Software, vol.23, p.12, 2008.

K. Cao, S. Boitard, and P. Besse, Sparse PLS Discriminant Analysis: biologically relevant feature selection and graphical displays for multiclass problems, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00959981

E. Yergeau, S. A. Schoondermark-stolk, E. L. Brodie, S. Déjean, T. Z. Desantis et al., Environmental microarray analyses of Antarctic soil microbial communities, The International Society for Microbial Ecology Journal, vol.3, issue.3, pp.340-351, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00529762

S. Combes, I. González, S. Déjean, A. Baccini, N. Jehl et al., Relationships between sensorial and physicochemical measurements in meat of rabbit from three different breeding systems using canonical correlation analysis, Meat Science, vol.3, pp.835-841, 2008.

K. Cao, I. González, and S. Déjean, integrOmics: an R package to unravel relationships between two omics data sets, Bioinformatics, vol.25, issue.21, pp.2855-2856, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00644862

I. González, K. Cao, M. J. Davis, and S. Déjean, Insightful graphical outputs to explore relationships between two 'omics' data sets, 2011.

, The UniProt Consortium, Ongoing and future developments at the Universal Protein Resource, Nucleic Acids Res, vol.38, pp.142-148, 2011.

R. Leinonen, F. G. Diez, D. Binns, W. Fleischmann, R. Lopez et al., UniProt archive. Bioinformatics, vol.20, pp.3236-3237, 2009.

. Be, H. Suzek, P. Huang, R. Mcgarvey, C. H. Mazumder et al., UniRef: comprehensive and non-redundant UniProt reference clusters, Bioinformatics, vol.23, pp.1282-1288, 2007.

S. Patient, D. Wieser, M. Kleen, E. Kretschmann, M. J. Martin et al., UniProtJAPI: a remote API for accessing UniProt data, Bioinformatics, vol.24, pp.1321-1322, 2008.

N. R. Anderson, Issues in biomedical research data management and analysis: needs and barriers, J Am Med Inform Assoc, vol.14, pp.478-488, 2007.

G. Bidaut and C. J. Stoeckert, Large scale transcriptome data integration across multiple tissues to decipher stem cell signatures, Methods Enzymol, vol.467, pp.229-245, 2009.

A. Brazma, Minimum Information About a Microarray Experiment (MIAME)--successes, failures, challenges, ScientificWorldJournal, vol.9, pp.420-423, 2009.

S. Myneni and V. L. Patel, Organization of Biomedical Data for Collaborative Scientific Research: A Research Information Management System, Int J Inf Manage, vol.30, pp.256-264, 2010.

J. Hue, X. He, K. Baggerly, K. Coombes, B. Hennessy et al., Non-parametric quantification of protein lysate arrays, Bioinformatics, vol.23, 1986.

N. Servant, E. Gravier, P. Gestraud, C. Laurent, C. Paccard et al., EMA: A R package to Easy Microarray data Analysis, vol.3, p.277, 2010.

. Ra, D. E. Gutiérrez, G. M. Shasha, and . Coruzzi, Systems Biology for the Virtual Plant, Plant Physiol, vol.138, pp.550-554, 2005.

. Sf, W. Altschul, . Gish, E. W. Miller, D. J. Myers et al., Basic local alignment search tool, J. Mol. Biol, vol.215, pp.403-410, 1990.

I. Romeuf, D. Tessier, M. Dardevet, G. Branlard, G. Charmet et al., wDBTF: an integrated database resource for studying wheat transcription factor families, BMC Genomics, vol.11, p.185, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00964124

C. Rustenholz, F. Choulet, C. Laugier, J. Safar, H. Simkova et al., A 3000-loci transcription map of chromosome 3B unravels the structural and functional features of gene islands in hexaploid wheat, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00964456

. Hw, A. Mewes, F. Ruepp, T. Theis, M. Rattei et al., MIPS: curated databases and comprehensive secondary data resources in 2010, Nucleic Acids Res, vol.39, pp.220-224, 2011.

I. Wheat-genome-sequencing and . Consortium, Guidelines for annotating wheat genomic sequences: release 1, 2006.

J. Vincent, P. Martre, C. Ravel, A. Baillif, and M. Agier, A web-oriented platform for gene regulatory network inference. Application to seed storage proteins in wheat

I. Romeuf, Identification in silico des facteurs de transcription du blé tendre (Triticum aestivum) et mise en évidence des facteurs de transcription impliqués dans la synthèse des protéines de réserve, 2010.

M. Reignier, A unified approach to word occurrences probabilities, Discrete Applied Mathematics, vol.104, issue.1, pp.259-280, 2000.

M. Lothaire, Statistics on Words with application to Biological Sequences, Applied Combinatorics on Words, 2005.

G. Nuel, Numerical solutions for Patterns Statistics on Markov chains, Stat. App. in Genet. and Mol. Biol, vol.5, issue.1, p.26, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00271482

P. Nicodème, B. Salvy, and P. Flajolet, Motif statistics. Theoretical Com. Sci, vol.287, issue.2, pp.593-617, 2002.

M. Crochemore and V. Stefanov, Waiting time and complexity for matching patterns with automata, INFO. PROC. LETTERS, vol.87, issue.3, pp.119-125, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00619588

M. E. Lladser, Mininal Markov chain embeddings of pattern problems, Information Theory and Applications Workshop, pp.251-255, 2007.

G. Nuel, Pattern Markov chains: optimal Markov chain embedding through deterministic finite automata, J. of Applied Prob, vol.45, issue.1, pp.226-243, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00271298

G. Nuel, On the first k moments of the random count of a pattern in a multi-states sequence generated by a Markov source, J. of Applied Prob, vol.47, pp.1-19, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00419038

L. Baena-lopez, A. Baonza, and A. Garcia-bellido, The orientation of cell divisions determines the shape of Drosophila organs, Curr. Biol, vol.15, pp.1640-1644, 2005.

S. Meilhac, M. Esner, M. Kerszberg, J. Moss, and M. Buckingham, Oriented clonal cell growth in the developing mouse myocardium underlies cardiac morphogenesis, J. Cell Biol, vol.164, pp.97-109, 2004.
URL : https://hal.archives-ouvertes.fr/pasteur-01573451

S. Pop, A. Dufour, J. F. Le-garrec, C. Ragni, M. Buckingham et al., A fast and automated framework for extraction of nuclei from cluttered 3D images in fluorescence microscopy, Proc. of IEEE Internat. Symposium on Biomedical Imaging: from Nano to Macro -ISBI2011, pp.2113-2116, 2011.

D. Cohen-steiner, P. Alliez, and M. Desbrun, Variational shape approximation, ACM Transact. On Graphics, vol.23, 2004.
URL : https://hal.archives-ouvertes.fr/inria-00070632

M. Giraud and J. Varré, Parallel position weight matrices algorithms, Parallel Computing, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00438215

G. Rizk and D. Lavenier, GPU accelerated rna folding algorithm, Proceedings of the 9th International Conference on Computational Science, pp.1004-1013, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00637827

M. Schatz, C. Trapnell, A. L. Delcher, and A. Varshney, High-throughput sequence alignment using graphics processing units, BMC Bioinformatics, vol.8, p.474, 2007.

S. Manavski and G. Valle, CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment, BMC Bioinformatics, vol.9, 2008.

H. Shi, B. Schmidt, W. Liu, and W. Mueller-wittig, A parallel algorithm for error correction in high-throughput short-read date on cuda-enabled graphics hardware, Journal of Computational Biology, vol.17, issue.4, pp.603-615, 2010.

Y. Liu, B. Schmidt, and D. L. Maskell, Parallel reconstruction of neighbor-joining trees for large multiple sequence alignments using cuda, Proceedings of the 8th IEEE International Workshop on High Performance Computational Biology, pp.1-8, 2009.

P. D. Vouzis and N. V. Sahinidis, GPU-BLAST : using graphics processors to accelerate protein sequence alignment, Bioinformatics, vol.27, issue.2, pp.182-188, 2011.

J. Varré, B. Schmidt, S. Janot, and M. Giraud, Advances in Genomic Sequence Analysis and Pattern Discovery, chapter Manycore high-performance computing in bioinformatics, 2011.

R. C. Holland, T. A. Down, and M. Pocock, BioJava : an open-source framework for bioinformatics. Bioinformatics, vol.24, pp.2096-2097, 2008.

J. E. Stajich, D. Block, and K. Boulez, The Bioperl toolkit : Perl modules for the life sciences, Genome Research, vol.12, issue.10, pp.1611-1618, 2002.

P. J. Cock, T. Antao, and J. T. Chang, Biopython : freely available Python tools for computational molecular biology and bioinformatics, p.163, 2009.

E. Roberts, J. Stone, L. Sepulveda, W. Hwu, and Z. Luthey-schulten, Long time-scale simulations of in vivo diffusion using GPU hardware, Proceedings of the 8th IEEE International Workshop on High Performance Computational Biology, pp.1-8, 2009.

P. Steffen, R. Giegerich, and M. Giraud, GPU parallelization of algebraic dynamic programming, Proceedings of the 8th International Conference on Parallel Processing and Applied Mathematics, pp.290-299, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00438219

J. Reeder, P. Steffen, and R. Giegerich, pknotsRG : RNA pseudoknot folding including near-optimal structures and sliding windows, Nucleic Acids Research, vol.35, issue.S2, pp.320-324, 2007.

T. H. Meuwissen, B. J. Hayes, and M. E. Goddard, Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps, 2001.

T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, 2009.

T. T. Wu, Y. F. Chen, T. Hastie, E. Sobel, and K. Lange, Genome-wide association analysis by lasso penalized logistic regression, bioinformatics, vol.25, 2009.

H. D. Bondell and B. J. Reich, Simultaneous regression shrinkage, variable selection and clustering of predictors with OSCAR, Biometrics, vol.64, pp.115-123, 2008.

C. Dhaenens and O. Combinatoire-multi-objectif, Apport des Méthodes Coopératives et Contributionà l'Extraction de Connaissances, 2005.

B. Néron, H. Ménager, C. Maufrais, N. Joly, J. Maupetit et al., Mobyle: a new full web bioinformatics framework, vol.25, pp.3005-3011, 2009.

K. Darty, A. Denise, and Y. Ponty, VARNA: interactive drawing and editing of the RNA secondary structure, Bioinformatics, vol.25, issue.15, 1974.
URL : https://hal.archives-ouvertes.fr/hal-00432548

M. Zuker, D. H. Mathews, and D. H. Turner, Algorithms and thermodynamics for RNA secondary structure prediction: a practical guide, RNA biochemistry and biotechnology, vol.70, pp.11-43, 1999.

T. Libourel, Y. Lin, I. Mougenot, C. Pierkot, and J. C. Desconnets, A Platform Dedicated to Share and Mutualize Environmental Applications, Proceedings of 12th International Conference on Enterprise Information Systems, 2010.
URL : https://hal.archives-ouvertes.fr/hal-02004954

Y. Lin, T. Libourel, and I. Mougenot, A Workflow Language for the Experimental Sciences, Proceedings of 11th International Conference on Enterprise Information Systems, 2009.
URL : https://hal.archives-ouvertes.fr/lirmm-00374850

I. Altintas, B. Ludäscher, S. Klasky, and M. A. Vouk, S04 -introduction to scientific workflow management and the kepler system, p.205, 2006.

D. Hull, K. Wolstencroft, R. Stevens, C. A. Goble, M. R. Pocock et al., Taverna: a tool for building and running workflows of services, Nucleic Acids Research, vol.34, pp.729-732, 2006.

, Meta Object Facility (MOF) Core Specification OMG Available Specification Version 2.0, OMG Document Number

, Infrastructure Version 2.3, OMG Document Number, OMG Unified Modeling LanguageTM (OMG UML)

, SPEM -Software & Systems Process Engineering Meta-Model Specification

M. , Bioside : faciliter l'accès des biologistes aux ressources bio-informatiques, JOBIM, Montréal, p.64, 2004.

P. Pinheiro-da-silva, L. Salayandia, and A. Q. Gates, WDO-It! A Tool for Building Scientific Workflows from Ontologies Departmental Technical Reports (CS), 2007.

L. Haibin and F. Yushun, CIMFlow: A Workflow Management System Based on Integration Platform Environment, Proceedings of 7th IEEE International Conference on Emerging Technologies and Factory Automation, pp.187-193, 1999.

S. Altschul, W. Gish, W. Miller, E. Myers, and D. Lipman, Basic local alignment search tool, Journal of Molecular Biology, vol.215, pp.403-410, 1990.

S. Guindon and O. Gascuel, A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood, Systematic Biology, vol.52, pp.696-704, 2003.

T. D. Schneider and R. M. Stephens, Sequence Logos: A New Way to Display Consensus Sequences, vol.18, pp.6097-6100, 1990.

G. A. Reeves, K. Eilbeck, M. Magrane, C. O'donovan, L. Montecchi-palazzi et al., The Protein Feature Ontology: a tool for the unification of protein feature annotations, Bioinformatics, vol.24, pp.2767-2772, 2008.

K. Eilbeck, S. Lewis, C. Mungall, M. Yandell, L. Stein et al., The Sequence Ontology: a tool for the unification of genome annotations, Genome Biology, vol.6, p.44, 2005.

M. Ashburner, C. A. Ball, J. A. Blake, D. Botstein, H. Butler et al., Gene ontology: tool for the unification of biology. The Gene Ontology Consortium, Nature Genetics, vol.25, pp.25-29, 2000.

T. M. Embley and W. Martin, Eukaryotic evolution, changes and challenges, Nature, vol.440, pp.623-653, 2006.

W. Martin and M. Müller, The hydrogen hypothesis for the first eukaryote, Nature, vol.392, pp.37-41, 1998.

T. Cavalier-smith, The origin of eukaryotic and archaebacterial cells, Ann N Y Acad Sci, vol.503, pp.17-54, 1987.

C. R. Woese, O. Kandler, and M. L. Wheelis, Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya, vol.87, pp.4576-4585, 1990.

J. A. Lake, E. Hendersen, M. Oakes, and M. W. Clark, Eocytes: a new ribosome structure indicates a kingdom with a close relationship to eukaryotes, vol.81, pp.3786-3790, 1984.

P. G. Foster, C. J. Cox, and T. M. Embley, The primary divisions of life: a phylogenomic approach employing composition-heterogeneous methods, Philos. Trans. R. Soc. Lond. B Biol. Sci, vol.364, pp.2197-207, 2009.

W. F. Doolittle, You are what you eat: a gene transfer ratchet could account for bacterial genes in eukaryotic nuclear genomes, Trends Genet, vol.14, pp.307-318, 1998.

L. Li, C. J. Stoeckert, J. , and D. S. Roos, OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes, Genome Res, vol.3, pp.2178-2189, 2003.

R. C. Edgar, Search and clustering orders of magnitude faster than BLAST, Bioinformatics, vol.26, issue.19, pp.2460-2461, 2010.

I. Uchiyama, Hierarchical clustering algorithm for comprehensive orthologous-domain classification in multiple genomes, Nucl. Acids Res, vol.34, issue.2, pp.647-658, 2003.

S. Goodswen, C. Gondro, N. Watson-haigh, and H. Kadarmideen, FunctSNP: an R package to link SNPs to functional knowledge and dbAutoMaker: a suite of Perl scripts to build SNP databases, BMC Bioinformatics, vol.11, issue.1, pp.311-311, 2010.

J. Reumers, S. Maurer-stroh, J. Schymkowitz, and F. Rousseau, SNPeffect v2.0: a new step in investigating the molecular phenotypic effects of human non-synonymous SNPs, vol.22, pp.2183-2185, 2006.

M. Ryan, M. Diekhans, S. Lien, Y. Liu, and R. Karchin, LS-SNP/PDB: annotated non-synonymous SNPs mapped to Protein Data Bank structures, Bioinformatics, vol.25, issue.11, pp.1431-1432, 2009.

M. Borodovsky and J. Mcininch, Recognition of genes in DNA sequence with ambiguities, Biosystems, vol.30, pp.161-171, 1993.

S. F. Altschul, T. L. Madden, A. A. Schaffer, J. Zhang, Z. Zhang et al., Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Nucleic Acids Res, vol.25, pp.3387-3402, 1997.

D. J. Sherman, T. Martin, M. Nikolski, C. Cayla, J. L. Souciet et al., Génolevures: protein families and synteny among complete hemiascomycetous yeast proteomes and genomes, Nucleic Acids Res, vol.36, pp.550-554, 2009.

L. D. Stein, The Generic Genome Browser: A building block for a model organism system database, Genome Res, vol.12, pp.599-1610, 2002.

D. Lawson, P. Arensburger, and P. Atkinson, VectorBase: a data resource for invertebrate vector genomics, Nucleic Acids Res, vol.37, pp.583-590, 2009.

M. Sharakhova, M. Hammond, and N. Lobo, Update of the Anopheles gambiae PEST genome assembly, Genome Biol, vol.8, issue.1, p.5, 2008.

V. Nene, J. Wortman, and D. Lawson, Genome sequence of Aedes aegypti, a major arbovirus vector, Science, vol.316, issue.5832, pp.1718-1741, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00156214

P. Arensburger, K. Megy, and R. Waterhouse, Sequencing of Culex quinquefasciatus establishes a platform for mosquito comparative genomics, Science, vol.330, issue.6000, pp.86-94, 2010.

E. Kirkness, B. Haas, and W. Sun, Genome sequences of the human body louse and its primary endosymbiont provide insights into the permanent parasitic lifestyle, Proc Natl Acad Sci, vol.107, issue.27, pp.12168-73, 2010.

V. Curwen, E. Eyras, and T. Andrews, The Ensembl automatic gene annotation system, Genome Res, vol.14, issue.5, pp.942-50, 2004.

S. Anders and W. Huber, Differential expression analysis for sequence count data, Genome Biology, vol.11, p.106, 2010.

B. Bolstad, R. Irizarry, M. Astrand, and T. Speed, A comparison of normalization methods for high density oligonucleotide array data based on bias and variance, Bioinformatics, vol.19, pp.185-193, 2003.

J. Bullard, E. Purdom, K. Hansen, and S. Dudoit, Evauation of statistical methods for normalization and differential expression in mRNA-seq experiments, BMC Bioinformatics, vol.11, p.94, 2010.

A. Mortazavi, B. Williams, K. Mccue, L. Schaeffer, and B. Wold, Mapping and quantifying mammalian transcriptomes by RNA-seq, Nature Methods, vol.5, pp.621-628, 2008.

A. Oshlack and M. J. Wakefield, Transcript length bias in RNA-seq data confounds systems biology, Biology Direct, vol.4, p.14, 2009.

M. Robinson and A. Oshlack, A scaling normalization method for differential expression analysis of RNA-seq data

, Genome Biology, vol.11, p.25, 2010.

T. Strub, S. Giuliano, T. Ye, C. Bonet, C. Keime et al., Essential role of microphtalmia transcription factor for DNA replication, mitosis and genomic stability in melanoma, Oncogene, 2011.

S. Anders and W. Huber, Differential expression analysis for sequence count data, Genome Biology, vol.11, p.106, 2010.

. Md, D. J. Robinson, G. K. Mccarthy, S. Smyth, and . Dudoit, edgeR : a Bioconductor package for differential expression analysis of digital gene expression data, Bioinformatics, vol.26, pp.136-140, 2009.

J. Qin, A human gut microbial gene catalogue established by metagenomic sequencing, Nature, vol.464, pp.59-70, 2010.
URL : https://hal.archives-ouvertes.fr/cea-00908974

D. Lawson, P. Arensburger, and P. Atkinson, VectorBase: a data resource for invertebrate vector genomics, Nucleic Acids Res, vol.37, pp.583-590, 2009.

B. Chevreux, T. Pfisterer, and B. Drescher, Using the miraEST Assembler for Reliable and Automated mRNA Transcript Assembly and SNP Detection in Sequenced ESTs, Genome Res, vol.14, pp.1147-1159, 2004.

B. Langmead, C. Trapnell, M. Pop, and S. L. Salzberg, Ultrafast and memory-efficient alignment of short DNA sequences to the human genome, Genome Biology, vol.10, p.25, 2009.

T. D. Wu and S. Nacu, Fast and SNP-tolerant detection of complex variants and splicing in short reads, Bioinformatics, vol.26, pp.873-881, 2010.

T. D. Wu and C. K. Watanabe, GMAP: a genomic mapping and alignment program for mRNA and EST sequences, Bioinformatics, vol.21, pp.1859-1875, 2005.

C. Trapnell, B. A. Williams, and G. Pertea, Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation, Nature Biotechnology, vol.28, pp.511-515, 2010.

M. Guttman, M. Garber, and J. Z. Levin, Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs, Nature Biotechnology, vol.28, pp.503-510, 2010.

L. Siegwald, F. Texier, and C. Hubans-pierlot, Development and optimization of metagenomic analyses, Journées Ouvertes Biologie Informatique Mathématiques, 2010.

E. Pruesse, C. Quast, K. Knittel, B. Fuchs, W. Ludwig et al., SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB, Nucleic Acids Res, vol.35, pp.7188-7196, 2007.

J. Schultz, T. Müller, M. Achtziger, P. N. Seibel, T. Dandekar et al., The internal transcribed spacer 2 database -a web server for (not only) low level phylogenetic analyses, Nucleic Acids Res, vol.34, pp.704-707, 2006.

D. Zerbino and E. Birney, Velvet: Algorithms for De Novo Short Read Assembly Using De Bruijn Graphs, Genome Research, vol.18, pp.821-829, 2008.

S. Anders and W. Huber, Differential expression analysis for sequence count data, Genome Biology, vol.11, p.106, 2010.

C. Trapnell, L. Pachter, and S. L. Salzber, TopHat: discovering splice junctions with RNA-Seq, Bioinformatics, vol.25, issue.9, pp.1105-1111, 2009.

A. Bertoni and G. Valentini, Model order selection for bio-molecular data clustering, BMC Bioinformatics, vol.8, issue.2, p.7, 2007.

S. Falcon and R. Gentleman, Using GOstats to test gene lists for GO term association, Bioinformatics, vol.23, pp.257-258, 2007.

S. Le, J. Josse, and F. Husson, Factominer: an R package for multivariate analysis, Journal of statistical software, vol.25, pp.1-18, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00359835

N. Servant, G. Eleonore, P. Gestraud, C. Laurent, C. Paccard et al., Ema -a R package for easy microarray data analysis, BMC Research Notes, vol.3, p.277, 2010.
URL : https://hal.archives-ouvertes.fr/inserm-00984710

V. G. Tusher, R. Tibshirani, and G. Chu, Significance analysis of microarrays applied to the ionizing radiation response, Proc Natl Acad Sci, vol.98, pp.5116-5137, 2001.

D. Bartel, MicroRNAs: genomics, biogenesis, mechanism and function, Cell, vol.116, pp.281-197, 2004.

S. A. Helvik, O. J. Snove, and P. Saetrom, Reliable prediction of Drosha processing sites improves microRNA gene prediction, Bioinformatics, vol.23, pp.142-149, 2007.

I. L. Hofacker, B. Priwitzer, and P. F. Stadler, Prediction of Locally Stable RNA Secondary Structures for Genome-Wide Surveys, Bioinformatics, vol.20, pp.186-190, 2004.

A. Sewer, N. Paul, P. Landgraf, A. Aravin, S. Pfeffer et al., Identification of clustered microRNAs using an ab initio prediction method, BMC Bioinformatics, vol.6, p.267, 2005.

B. K. Hammer and B. L. Bassler, Regulatory small RNAs circumvent the conventional quorum sensing pathway in pandemic Vibrio cholerae, Proc Natl Acad Sci U S A, vol.104, issue.27, pp.11145-11154, 2007.

B. Langmead, C. Trapnell, M. Pop, and S. L. Salzberg, Ultrafast and memory-efficient alignment of short DNA sequences to the human genome, Genome Biol, vol.10, issue.3, p.25, 2009.

P. P. Gardner, J. Daub, J. G. Tate, E. P. Nawrocki, D. L. Kolbe et al., Rfam: updates to the RNA families database, Nucleic Acids Res, vol.37, pp.136-176, 2009.

J. Livny, H. Teonadi, M. Livny, and M. K. Waldor, High-throughput, kingdom-wide prediction and annotation of bacterial non-coding RNAs, PLoS One, vol.3, p.3197, 2008.

A. Marchais, M. Naville, C. Bohn, P. Bouloc, and D. Gautheret, Single-pass classification of all noncoding sequences in a bacterial genome using phylogenetic profiles, Genome Res, vol.19, pp.1084-92, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00529723

J. M. Liu, J. Livny, M. S. Lawrence, M. D. Kimball, M. K. Waldor et al., Experimental discovery of sRNAs in Vibrio cholerae by direct cloning, 5S/tRNA depletion and parallel sequencing, Nucleic Acids Res, vol.37, p.46, 2009.

H. Abdi, Metric multidimensional scaling, Encyclopedia of Measurement and Statistics, pp.598-605, 2007.

W. S. Togerson, Theory and methods of scaling, 1958.

J. Pelé, H. Abdi, M. Moreau, D. Thybert, and M. Chabbert, Multidimensional scaling reveals main evolutionary determinants and class A G-protein-coupled receptors, PloS one, 2011.

J. C. Gower, Adding a Point to Vector Diagrams in Multivaraiate Analysis Biometrika, vol.55, pp.582-585, 1968.

S. H. Kappe, A. M. Vaughan, J. A. Boddey, and A. F. Cowman, That Was Then but This Is Now: Malaria Research in the Time of an Eradication Agenda, Science, vol.328, issue.5980, pp.862-866, 2010.

S. Soni, S. Dhawan, K. M. Rosen, M. Chafel, A. H. Chishti et al., Characterization of Events Preceding the Release of Malaria Parasite from the Host Red Blood Cell, Blood Cells Mol. and Dis, vol.35, issue.2, pp.201-211, 2005.

E. Verissimo, N. Berry, P. Gibbons, M. L. Cristiano, P. J. Rosenthal et al., Design and Synthesis of Novel 2-Pyridone Peptidomimetic Falcipain 2/3 Inhibitors, Bioorg. & Med. Chem. Lett, vol.18, issue.14, pp.4210-4214, 2008.

R. Ettari, E. Nizi, M. E. Di-francesco, M. Dude, G. Prade et al., Development of Peptidomimetics with a Vinyl Sulfone Warhead as Irreversible Falcipain-2 Inhibitors

, J Med Chem, vol.51, issue.4, pp.988-996, 2008.

R. Ettari, N. Micale, T. Schirmeister, C. Gelhaus, M. Leippe et al., Novel Peptidomimetics Containing a Vinyl Ester Moiety as Highly Potent and Selective Falcipain

. Inhibitors, J Med Chem, vol.52, issue.7, pp.2157-2160, 2009.

P. V. Desai, A. Patny, J. Gut, P. J. Rosenthal, B. Tekwani et al., Identification of Novel Parasitic Cysteine Protease Inhibitors by Use of Virtual Screening. 2. The Available Chemical Directory, J Med Chem, vol.49, issue.5, pp.1576-1584, 2006.

J. Zhu, T. Chen, L. Chen, W. Lu, P. Che et al., 2-Amido-3-(1h-Indol-3-Yl)-N-Substitued-Propanamides as a New Class of Falcipain-2 Inhibitors. 1. Design, Synthesis, Biological Evaluation and Binding Model Studies, Molecules, vol.14, issue.1, pp.494-508, 2009.

F. Boutrot, N. Chantret, and M. F. Gautier, Genome-wide analysis of the rice and Arabidopsis non-specific lipid transfer protein (nsLtp) gene families and identification of wheat nsLtp genes by EST data mining, BMC Genomics, vol.9, p.86, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02667808

A. Sali and T. L. Blundell, Comparative protein modelling by satisfaction of spatial restraints, J Mol Biol, vol.234, pp.779-815, 1993.

C. Fleury, V. Moreau, L. Felicori, S. Pérès, P. S. Beirão et al.,

A. R. Ortiz, C. E. Strauss, and O. Olmea, MAMMOTH (matching molecular models obtained from theory): an automated method for model comparison, Protein Sci, vol.11, pp.2606-2621, 2002.

O. Lichtarge, H. Bourne, and F. E. Cohen, An evolutionary trace method defines binding surfaces common to protein families, J Mol Biol, vol.257, pp.342-358, 1996.

P. Melke, H. Jönsson, E. Pardali, P. Dijke, and C. Peterson, A rate equation approach to elucidate the kinetics and robustness of the TGF-beta pathway, Biophysical journal, vol.91, pp.4368-80, 2006.

B. Schmierer, A. L. Tournier, P. Bates, and C. S. Hill, Mathematical modeling identifies Smad nucleocytoplasmic shuttling as a dynamic signal-interpreting system, Proceedings of the National Academy of Sciences of the United States of America, vol.105, pp.6608-6621, 2008.

J. M. Vilar, R. Jansen, and C. Sander, Signal processing in the TGF-beta superfamily ligand-receptor network, PLoS computational biology, vol.2, p.3, 2006.

S. Zibaee, O. S. Makin, M. Goedert, and L. C. Serpell, A simple algorithm locates beta-strands in the amyloid fibril core of alpha-synuclein, Abeta, and tau using the amino acid sequence alone, Protein Sci, vol.16, pp.906-918, 2007.

J. Tian, N. Wu, J. Guo, and Y. Fan, Prediction of amyloid fibril-forming segments based on a support vector machine, BMC Bioinformatics, vol.30, 2009.

S. O. Garbuzynskiy, M. Y. Lobanov, and O. V. Galzitskaya, FoldAmyloid: a method of prediction of amyloidogenic regions from protein sequence, Bioinformatics, vol.26, pp.326-332, 2010.

S. Maurer-stroh, M. Debulpaep, N. Kuemmerer, M. Lopez-de-la-paz, I. C. Martins et al., Exploring the sequence determinants of amyloid structure using position-specific scoring matrices, Nat Methods, vol.7, pp.237-242, 2010.

A. L. Béchec, A. Talvas, E. Rio, M. Emily, C. Garnier et al., A large scale comparison of predicted amyloigogenic regions using several published methods, 2010.

T. Rose, A. Pillet, V. Lavergne, B. Tamarit, P. Lenormand et al., Interleukin-7 compartmentalizes its receptor signaling complex to initiate CD4 T lymphocyte response, J Biol Chem, vol.285, pp.14898-14908, 2010.

J. Villén, S. A. Beausoleil, and S. P. Gygi, Evaluation of the utility of neutral-loss-dependent MS3 strategies in largescale phosphorylation analysis, Proteomics, vol.8, issue.21, pp.4444-52, 2008.

. Pj-ulintz, B. Yocum, . Bodenmiller, P. C. Aebersold, A. I. Andrews et al., Comparison of MS(2)-only, MSA, and MS(2)/MS(3) methodologies for phosphopeptide identification, J Proteome Res, vol.8, issue.2, pp.887-99, 2009.

. Dn-perkins, D. J. Pappin, D. M. Creasy, and J. S. Cottrell, Mascot: Probability-based protein identification by searching sequence databases using mass spectrometry data, Electrophoresis, vol.20, issue.18, pp.3551-67, 1999.

. Mm-savitski, M. Lemeer, . Boesche, . Lang, M. Mathieson et al., Confident phosphorylation localization site using the Mascot Delta Score, Mol Cell Proteomics, vol.10, issue.2, pp.3830-3831, 2011.

S. Yilmaz, P. Jonveaux, C. Bicep, L. Pierron, M. Smaïl-tabbone et al., Gene-disease relationship discovery based on model-driven data integration and database view definition, Bioinformatics, vol.25, pp.230-236, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00359111

D. Smedley, M. A. Swertz, K. Wolstencroft, G. Proctor, M. Zouberakis et al., Solutions for data integration in functional genomics: a critical assessment and case study, Brief Bioinform, vol.9, pp.532-576, 2008.

J. A. Vizcaíno, F. Reisinger, R. Côté, and L. Martens, Database on Demand" as valuable tools for computational proteomics, Methods Mol Biol, vol.696, pp.93-105, 2011.

A. Friedrich, N. Garnier, N. Gagnière, H. Nguyen, L. P. Albou et al., SM2PH-db: an interactive system for the integrated analysis of phenotypic consequences of missense mutations in proteins involved in human genetic diseases, Human Mutation, vol.31, pp.127-135, 2010.

D. Luu, H. Nguyen, A. Friedrich, J. Muller, L. Moulinier et al., Extracting Knowledge from a Mutation Database Related to Human Monogenic Disease Using Inductive Logic Programming, Proceedings of the International Conference on Bioscience, 2011.

P. Andrey, E. Maschino, and Y. Maurin, Spatial normalisation of three-dimensional neuroanatomical models using shape registration, averaging, and warping, Fifth IEEE International Symposium on Biomedical Imaging (ISBI'08): From Nano to Macro, pp.1183-1186, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02756733

P. Andrey and Y. Maurin, Free-D: an integrated environment for three-dimensional reconstruction from serial sections, J. Neurosci. Methods, vol.145, issue.1-2, pp.233-244, 2005.
URL : https://hal.archives-ouvertes.fr/hal-02681457

E. Biot, E. Crowell, H. Höfte, Y. Maurin, S. Vernhettes et al., A new filter for spot extraction in Ndimensional biological imaging, Fifth IEEE International Symposium on Biomedical Imaging (ISBI'08): From Nano to Macro, pp.975-978, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02758229

J. Burguet, P. Andrey, O. Rampin, and Y. Maurin, Three-dimensional statistical modeling of neuronal populations: illustration with spatial localization of supernumerary neurons in the locus coeruleus of quaking mutant mice, J. Comp. Neurol, vol.513, issue.5, pp.483-495, 2009.
URL : https://hal.archives-ouvertes.fr/hal-02659576

J. Burguet, P. Mailly, Y. Maurin, and P. Andrey, Reconstructing the three-dimensional surface of a branching and merging biological structure from a stack of coplanar contours, Eighth IEEE International Symposium on Biomedical Imaging, 2011.
URL : https://hal.archives-ouvertes.fr/hal-02750403

E. Maschino, Y. Maurin, and P. Andrey, Joint registration and averaging of multiple 3D anatomical surface models, Comput. Vis. Image Underst, vol.101, issue.1, pp.16-30, 2006.
URL : https://hal.archives-ouvertes.fr/hal-02665683

E. R. Mardis, A decade's perspective on DNA sequencing technology, Nature, vol.10, 2011.

E. Pennisi, Human genome 10th anniversary. Will computers crash genomics?, Science, vol.331, pp.666-668, 2011.

. Ee, M. D. Schadt, J. Linderman, L. Sorenson, G. P. Lee et al., Computational solutions to large-scale data management and analysis, Nat. Rev. Genet, vol.11, pp.647-657, 2010.

. Gk and . Smyth, Linear models and empirical bayes methods for assessing differential expression in microarray experiments, Stat Appl Genet Mol Biol, vol.3, 2004.

. Renabi-grisbi--infrastructure-distribuée-pour-la-bioinformatique,

C. Blanchet-1, G. Clément, and C. Olivier, Stéphane DELMOTTE, vol.3

, Infrastructure Distribuée pour la Biologie, IDB IBCP FR3302 CNRS, 7 passage du Vercors, vol.69007

F. Abims, S. Cnrs-upmc, . Biologique, G. Place, and . Teissier, , 29680.

C. Genouest, C. Irisa--umr6074, and . De-beaulieu, RENNES Cedex -France, vol.35042

U. Lbbe and . Cnrs, 43 bd du 11 novembre 1918, 69622 VILLEURBANNE cedex, France {stephane.delmotte, bruno.spataro}@univ-lyon1

U. Labri and . Cnrs, 351 cours de la Libération, vol.33400

M. Migale, I. Et-génome, and . Inra,

K. Bioinformatique, Infrastructure distribuée, Calcul scientifique

R. Prabi, R. Renabi-ne, and . Aplibio, La couche logicielle de l'infrastructure GRISBI s'appuie sur le logiciel de grille européen gLite (www.glite.org), en collaboration avec l, L'infrastructure GRISBI (www.grisbio.fr) est une initiative conjointe entre plusieurs centres de Bioinformatique

G. Les, . Ibisa, and . Francegrilles, L'utilisation de l'infrastructure par la communauté relève de différents domaines comme l'analyse NGS, la génomique comparative, la biologie des systèmes, la prédiction de fonction de protéines ou les interactions moléculaires. Notamment, un pilote de mise en oeuvre d'expériences NGS est en cours avec une , qui sert d'interlocuteur et de guide pour l'utilisation des ressources Remerciements: Delphine Naquin, Christelle Eloto

O. Filangi, Y. Beausse, A. Assi, L. Legrand, J. M. Larré et al., BioMAJ: A flexible framework for databanks synchronization and processing, Bioinformatics, vol.24, pp.1823-1825, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00327502

E. Vieira-silva and . .. Rocha,

C. Petitjean, P. Brochier-armanet, D. López-garcia, and .. .. Moreira, Horizontal Gene Transfer of a Chloroplast Protein to Thaumarchaeota: The Unique Case of a Ferredoxine and a J-domain Fusion C

, Tpms: a Tree Pattern-Matching Utility for Querying Gene Trees Collections T. Bigot

V. Inizan, S. Jamilloux, T. Arnoux, H. Flutre, and . .. Quesneville, Combined Approach for Transposable Elements Detection O

P. Genomes-using, E. E. Sallet, J. Gouzy, B. Roux, D. Capela et al., Integrated Gene Prediction for

J. Functional-genome-annotation, M. Amselem, N. Alaux, N. Choisne, B. Lapalu et al., URGI Genome Annotation System: an Integrated System for Structural

M. Lebrun, D. Steinbach, H. .. Quesneville, M. Moreira, G. Turcotte et al., 119 NGS: Neglected Genome Sequencing. Assembly and Annotation Challenges in a Highly Divergent Protozoan Genome

, Influence Function for Robust Phylogenetic Reconstruction M. Mariadassou and A

A. .. Criscuolo,

J. Wang, O. Elsen, P. Filangi, and . .. Roy,

, Rearrangements Occur Mostly Neutrally in Eukaryotic Genomes C. Berthelot, M. Muffato and H

A. Friedrich, C. Reisser, P. Jung, and J. .. Schacherer, Genetic Diversity of the Lachancea kluyveri Yeast Species

E. .. Rocha, 169 Identification of Putative Parasitism Genes in Plant-Parasitic Nematodes

A. Campan-fournier, L. Perfus-barbeoch, M. Rosso, M. Arguel, C. Silva et al.,

M. Schmidt, B. Wilson, P. Ballester, G. Schwalie, A. Brown et al., Five Vertebrate ChIP-seq Reveals the Evolutionary Dynamics of Transcription Factor Binding D

S. Martinez-jimenez, I. Mackay, P. Talianidis, D. Flicek, and .. .. Odom,

A. Vera-licona, I. Zinovyev, O. Kuperstein, A. Kel, T. Kel et al., An Integrative Signaling Pathway Analysis for Determining Master Regulators and Dysregulated Pathways in Her2 Over-Expressed Human Breast Cancer P, p.39

M. Proteome, A. Comparative-analysis, P. Iltis, F. Ciron, and . .. Rechenmann,

G. Meil, P. Kerbellec, and . .. Durand, Mining Databanks to Analyse Functional and Taxonomic Diversity of Sequences A

. Large-scale, Phylogenomic Analyses Indicate a Deep Origin of Primary Plastids within Cyanobacteria A. Criscuolo and

, Estimating Phylogenetic Correlations between Molecular Data and Longevity in Mammals R. Poujol and

P. Signaling-systems-in-bilaterian-genomes, O. Mirabeau, and J. .. Joly,

S. Meta-populations, M. Brouillet, F. Kearney, J. Maldarelli, G. Coffin et al.,

J. Yengo, C. Jacques, and . .. Biernacki, A Block Regression Approach for Simultaneous Variables Clustering and Selection: Application to Genetic Data L

H. S. Host, N. Parto, . .. Lartillot, C. Goudot, F. Etchebest et al., Cross-Species Comparison of cis-Regulatory Motifs: the Case Study of AP-1 Transcription Factors in Yeasts C, Differential Selection Profiles using Statistical Phylogenetic Models for Understanding HIV Adaptation According to

D. Their-adaptive-gene-reservoirs, E. Goudenège, E. Krin, C. Corre, D. Médigue et al., TriAnnot: a High Performance Pipeline for the Automated Structural and Functional Annotation of Plant Genomes, Vibrios Infecting Marine Invertebrates: New Insights into Vibrio Virulence, vol.215, p.111

H. Itoh, C. Quesneville, and . .. Feuillet,

. .. Bibliolist-;-quevillon,

R. Saidi, W. Dhifli, S. Aridhi, M. Agier, G. Bronner et al.,

. .. Mephu-nguifo, Predicting Copy Number Alterations and Structural Variants Using Paired-End Sequencing Data V, p.223

P. Cahais, G. Gayral, J. Tsagkogeorga, Y. Melo-ferreira, K. Chiari et al., De Novo Transcriptome Assembly in Non-Model Organisms from Next Generation Sequencing Data V, p.225

, Analyzing RNA-Seq Data within the MicroScope Web-based Platform

B. Chane-woon-ming, M. Weiman, D. Vallenet, V. De, B. Berardinis et al.,

. .. Médigue, A. Baron, R. Bihouée, E. Teusan, F. Dubois et al., Integration and Analysis of Gene Identifier Lists D, p.231

S. Mouysset, J. Noailles, D. Ruiz, and R. .. Guivarch, Microarray Image Segmentation Using Parallel Spectral Clustering

, Validated Chip Annotation: a New Tool for Gene Annotation Quality Control G. Jules-Clément, Improving Biclustering for High Dimension Genomic Data Using the Ensemble Methods B. Hanczar and M, vol.235

M. Garcia, O. Stahl, P. Finetti, F. Bertucci, D. Birnbaum et al., Biomarkers Discovery in Breast Cancer by Interactome-Transcriptome Integration

R. Of-non-coding, A. Cros, J. De-monte, P. Mariette, D. Bardou et al., Dynamics of Small RNA-Directed DNA Methylation During the Arabidopsis Innate Immune Response A, RNAspace: an Integrated Environment for the Prediction, Annotation and Analysis

, An Automatic Method for Identifying TE-derived miRNAs

S. Tempel, F. .. Tahi, S. Kim, J. Han, P. Bellay et al., Conserved Disorder: its Role in Human Disease and Common Variations M. Michaut

J. Jestin and C. .. Soulé,

I. Rabearivelo and F. .. Paillier,

, Bioinformatics Tools to Decrypt Pyoverdine Biosynthesis in Pseudomonas sp

A. Vanvlassenbroeck, V. Leclère, M. Pupin, B. Wathelet, and P. .. Jacques,

C. Etchebest, A. Bornot, A. De-brevern, and .. .. , Predicting Protein Flexibility through the Prediction of Local Structures
URL : https://hal.archives-ouvertes.fr/inserm-00568171

J. Joseph, N. Gelly, A. Srinivasan, and .. .. De-brevern, Protein 3D Structure Comparison Based on Sequence Alignment Approaches: Application of a Structural Alphabet A

R. Samson, C. Shrager, V. Tai, J. Sam, B. Gibrat et al., DOMIRE, a Web Server for Structural Domain Identification in Proteins F

P. Polymorphisms, V. Poulain, C. Jallu, A. Kaplan, and .. .. De-brevern, The Sequence-Structure Relationship in ?-helical, Silico Insights into the Platelet Alloimmune Response to ?IIb?3

E. Selwa, E. Laine, and T. .. Malliavin, Conformational Plasticity of the Adenylyl Cyclase CyaA from Bordetella Pertussis

N. D-alanine-ligase, D. Duclert-savatier, A. Meziane-cherif, M. Blondel, T. Nilges et al., The Dynamics Modes of the VanA D-alanyl:D-lactate Ligase are Similar to those of the D-alanyl

, Analysis of the Full Orthosteric Cavity to Discriminate Agonist from Antagonist Ligands in AChBP J. Buratti, A. Blondel, T. Malliavin and M

F. Convergence, C. Mareuil, T. Blanchet, M. Malliavin, and . .. Nilges, Developments in NMR Structure Calculation Protocol in Order to Improve the Structure Quality and

, The Superfamily of Beta-and Gamma-Crystallins: Evolution History and Sequence-Structure-Function Relationships E. Duprat, W. Luscap, F. Skouri-Panet and

, Enzyme Classification Using 3D Signatures of Protein Binding Site A

, Protein Structure Prediction with a Half Coarse Grained Model and Empirical Functions T. Bitard Feildel, A. Vigneron and

, Can Aspecific Docking Predict Protein-Protein Binding Sites ?

J. .. Martin, N. Stratmann, M. Prudhomme, J. Chlioui, M. Pathmanathan et al., Graph Clustering Analysis of a Boolean Model : Case of Iron Homeostasis in Saccharomyces cerevisiae M. Neri, J. Camadro and, vol.287, p.202

M. Rieu, Y. .. Bouc, P. Vincent, C. Martre, A. Ravel et al., Analysis of the Functionalization Process for Duplicated Genes of Arabidopsis thaliana in Protein-Protein Interactions Network and, vol.291, p.207

B. Bely, E. Stanley, M. .. Martin, !. Joomla, . Cms-o et al., Djeen: a High Throughput Multi-Technological Research Information Management System for the, biomanycores.org: Open-Source Parallel Bioinformatics, vol.321, p.218

;. Mgx--montpellier-genomix, C. Tools, J. Dantec, E. Desvignes, G. Dubois et al., Next Generation Sequencing and Microarray Facility Integrating Data Production and Analysis, p.335

J. To-mine-high-throughput-genotyping-data, C. Hamon, J. Dhaenens, G. Jacques, and . .. Even, Combining Combinatorial Optimization and Statistics

H. Ménager, V. Gopalan, B. Néron, S. Larroudé, J. Maupetit et al., , p.339

, An Organizational Environment for

M. .. Gouy, The COaLA Model: a Time Non-Homogeneous Model of Evolution Based on a Correspondance Analysis M

N. Phylogenies, A. Fiorini, F. Bisch, M. Dumond, F. Agbessi et al., PELICAN: Orthologous Groups and Gene Lateral Transfers for Comparative Genomic Analysis of Marine Cyanobacteria C, A Web-based Collaborative Platform for Comparing, vol.353, p.354

F. Lecerf, A. Bretaudeau, O. Sallou, C. Desert, Y. Blum et al., Génolevures : Policy for Automated Annotation of Genome Sequences T, AnnotQTL: a New Tool to Gather Functional and Comparative Information on a Genomic Region, vol.355, p.156

, RNA-seq Data Analysis: Lost in Normalization ?

M. Dillies and .. .. Statomique-consortium,

A. , J. .. Daudin, G. Sabbah, C. Mazo, F. Paccard et al., SMETHILLIUM: Spatial normalisation METHod for ILLumina InfinIUM HumanMethylation BeadChip C, vol.359, p.160

G. -seq, D. Koscielny, K. Hughes, D. Megy, D. Wilson et al., Improving Mosquito Genome Annotation using RNA

L. La-métagénomique, F. Siegwald, C. Texier, and .. .. Hubans-pierlot, RNA-Seq without a Reference Genome: a Comparison of the Mapping and the Assembly Approaches M, Importance des Banques de Séquences pour

S. Cezard, D. Mctaggart, M. Allen, U. Thomsom, M. Trivedi et al.,

N. Ema--a-r-package-for-easy-microarray-data-analysis, E. Servant, P. Gravier, C. Gestraud, C. Laurent et al.,

P. Barillot and . .. Hupé,

F. Tempel and . .. Tahi, Characterizing Novel Non-Coding Transcripts in Eukaryotic Genomes Using RNA-Seq Data M. Descrimes, Z. Saci

A. Ott, A. Idali, A. Marchais, D. .. Gautheret, C. Toffano-nioche et al., Interaction Profile of Small Inhibitors Complexed with Falcipain-2 and Falcipain-3 Plasmodial Cysteine Proteases P. Da Silva Figueiredo Celestino, Screening Bacterial Regulatory RNAs and their Targets Using Evolutionary Profiles, vol.368, p.169

. Bce), . Rmn, J. Et-dynamique-moléculaire, M. Cognet, G. Baouendi et al., FragMixer: A Modular Framework for (Phospho)peptide Identification from Multiple MS/MS Fragmentation Modes, Patho-genes.org : Collecte et Analyse des Amorces de PCR Utilisées pour la Détection des Micro-organismes Pathogènes J. Gardès, vol.375, p.257, 2011.

E. Alamyar, V. Giudicelli, P. Duroux, M. .. Lefranc, N. Luu et al., SM2PH-kb: Data Warehouse Intelligence for the Integrated Study of Human Structural Mutation to Phenotypes Relationships T, Three-dimensional Modeling Software for Group-wise Data Integration and Analysis of Spatial Distributions in Biological Imaging E. Biot, J. Burguet and, vol.384, p.389

C. Blanchet, . .. Loomis, N. F. Donnéees, A. Maurier, T. Groppi et al., 391 MGCA: a Flexible Tool for Phylogenomic Analyses of Prokaryotic Genomes K

D. Adaptive-gene-reservoirs, E. Goudenège, E. Krin, C. Corre, D. Médigue et al., Vibrios Infecting Marine Invertebrates: New Insights into Vibrio Virulence and their

, High Performance Pipeline for the Automated Structural and Functional Annotation of Plant Genomes

H. Itoh, C. Quesneville, and . .. Feuillet,

. .. Bibliolist-;-quevillon,

, Protein Classification in the Case of Large and Many-Class Datasets: A Comparison with BLAST and BLAT

R. Saidi, W. Dhifli, S. Aridhi, M. Agier, G. Bronner et al.,

. .. Mephu-nguifo,

B. Boeva, K. Zeitouni, A. Bleakley, J. Zinovyev, I. Vert et al., Predicting Copy Number Alterations and Structural Variants Using Paired-End Sequencing Data V, p.223

P. Cahais, G. Gayral, J. Tsagkogeorga, Y. Melo-ferreira, K. Chiari et al., De Novo Transcriptome Assembly in Non-Model Organisms from Next Generation Sequencing Data V, p.225

M. Chane-woon-ming, D. Weiman, V. Vallenet, . De, B. Berardinis et al., Analyzing RNA-Seq Data within the MicroScope Web-based Platform B

. .. Médigue, A. Baron, R. Bihouée, E. Teusan, F. Dubois et al., 227 Integration and Analysis of Gene Identifier Lists D, p.231

S. Mouysset, J. Noailles, D. Ruiz, and R. .. Guivarch, Microarray Image Segmentation Using Parallel Spectral Clustering

, Validated Chip Annotation: a New Tool for Gene Annotation Quality Control G. Jules-Clément, Improving Biclustering for High Dimension Genomic Data Using the Ensemble Methods B. Hanczar and M

M. Garcia, O. Stahl, P. Finetti, F. Bertucci, D. Birnbaum et al., Biomarkers Discovery in Breast Cancer by Interactome-Transcriptome Integration

M. Cros, A. De-monte, J. Mariette, P. Bardou, D. Gautheret et al., RNAspace: an Integrated Environment for the Prediction, Annotation and Analysis of Non-Coding RNA
URL : https://hal.archives-ouvertes.fr/hal-02810153

L. Abraham, A. Yu, G. Lepère, and L. .. Navarro, Dynamics of Small RNA-Directed DNA Methylation During the Arabidopsis Innate Immune Response A

F. .. Tahi, S. Kim, J. Han, P. Bellay, and . .. Kim, 253 Sets of Symmetries by Base Substitutions in the Genetic Code J, Conserved Disorder: its Role in Human Disease and Common Variations M. Michaut

I. Rabearivelo and F. .. Paillier,

, Bioinformatics Tools to Decrypt Pyoverdine Biosynthesis in Pseudomonas sp

A. Vanvlassenbroeck, V. Leclère, M. Pupin, B. Wathelet, and P. .. Jacques,

C. Etchebest, A. Bornot, A. De-brevern, and .. .. , Predicting Protein Flexibility through the Prediction of Local Structures
URL : https://hal.archives-ouvertes.fr/inserm-00568171

J. Joseph, N. Gelly, A. Srinivasan, and .. .. De-brevern, Protein 3D Structure Comparison Based on Sequence Alignment Approaches: Application of a Structural Alphabet A

R. Samson, C. Shrager, V. Tai, J. Sam, B. Gibrat et al., DOMIRE, a Web Server for Structural Domain Identification in Proteins F

P. Polymorphisms, V. Poulain, C. Jallu, A. Kaplan, and .. .. De-brevern, Silico Insights into the Platelet Alloimmune Response to ?IIb?3

J. Esque, A. Urbain, C. Etchebest, A. De-brevern, and .. .. , The Sequence-Structure Relationship in ?-helical Transmembrane Proteins

E. Selwa, E. Laine, and T. .. Malliavin, Conformational Plasticity of the Adenylyl Cyclase CyaA from Bordetella Pertussis

N. D-alanine-ligase, D. Duclert-savatier, A. Meziane-cherif, M. Blondel, T. Nilges et al., The Dynamics Modes of the VanA D-alanyl:D-lactate Ligase are Similar to those of the D-alanyl

, Analysis of the Full Orthosteric Cavity to Discriminate Agonist from Antagonist Ligands in AChBP J. Buratti, A. Blondel, T. Malliavin and M

, Developments in NMR Structure Calculation Protocol in Order to Improve the Structure Quality and Convergence F. Mareuil, C. Blanchet, T. Malliavin and M

, The Superfamily of Beta-and Gamma-Crystallins: Evolution History and Sequence-Structure-Function Relationships E. Duprat, W. Luscap, F. Skouri-Panet and

, Enzyme Classification Using 3D Signatures of Protein Binding Site A

, Protein Structure Prediction with a Half Coarse Grained Model and Empirical Functions T. Bitard Feildel, A. Vigneron and

, Can Aspecific Docking Predict Protein-Protein Binding Sites ?

J. .. Martin, N. Stratmann, M. Prudhomme, J. Chlioui, M. Pathmanathan et al., 285 Analysis of Protein-protein Interactions at the Subdomain Level D

M. Neri, J. Camadro, D. Mestivier, and .. .. , Graph Clustering Analysis of a Boolean Model : Case of Iron Homeostasis in Saccharomyces cerevisiae

A. Paris, B. Labrador, F. Lejeune, A. Zoubai, C. Canlet et al.,

M. Rieu and Y. .. Bouc, 291 A Web-Oriented Platform for Gene Regulatory Network

F. Rügheimer, A. Anand, and B. .. Schwikowski, A Software Architecture for de Novo Induction of Regulatory Networks from Expression Data

M. Systems-with-biorica, R. Assar, A. Garcia, D. Sherman, and .. .. ,

C. Chapple, B. Robisson, C. Herrmann, and C. .. Brun, MoonGO: Predicting Moonlighting Proteins from PPi Networks Based on GO Annotations

T. Data, J. Whalley, E. Birmelé, C. Devauchelle, and C. .. Rizzon, Analysis of the Functionalization Process for Duplicated Genes of Arabidopsis thaliana in Protein-Protein Interactions Network

C. Sorgodb:-superoxide-reductase-gene-ontology-curated-database, D. Lucchetti-miganeh, D. Goudenège, G. Thybert, F. Salbert et al.,

F. Research, L. Lejeune, F. Mesrob, C. Parmentier, J. Bicep et al., The Biogemix Knowledge Base Project: Cross-Species and Network-Based Data Integration for Huntington's Dis

M. Zasadzinski, F. Jacquemot, D. Mazur, Y. Fleury, M. Berchi et al., 315 mixOmics: an R Package for the Integration of 'omics' Data I. González, K.-A. Lê Cao and, SIDR, a Public Data Repository for Multi-Assay Experiments: Issues on Metadata Biocuration A

B. .. Bost,

B. Bely, E. Stanley, and M. .. Martin,

!. Joomla, A. Stahl, F. Guille, P. Blondin, S. Finetti et al., 325 dbWFA: A Web-Based Database for Functional Annotation of Wheat Transcripts, Djeen: a High Throughput Multi-Technological Research Information Management System for the

. .. Nuel, 329 3D Axis Clustering for Mapping Cell Polarity in the Complex Geometry of the Heart, 331 biomanycores.org: Open-Source Parallel Bioinformatics

;. Mgx--montpellier-genomix, C. Tools, J. Dantec, E. Desvignes, G. Dubois et al., Next Generation Sequencing and Microarray Facility Integrating Data Production and Analysis, p.335

J. To-mine-high-throughput-genotyping-data, C. Hamon, J. Dhaenens, G. Jacques, and . .. Even, Combining Combinatorial Optimization and Statistics

, New Types of Services in Mobyle, vol.1, issue.0

H. Ménager, V. Gopalan, B. Néron, S. Larroudé, J. Maupetit et al., , p.339

, An Organizational Environment for

K. Vectorbase, D. Megy, D. Lawson, G. Hughes, D. Koscielny et al., Vector Genome Annotation at

, RNA-seq Data Analysis: Lost in Normalization ? M.-A. Dillies and .. Statomique Consortium

J. Ngs-data, J. Aubert, . .. Daudin, G. Sabbah, C. Mazo et al., On the Use of the Negative Binomial Regression Model for Comparing Differential Expression or Abundance with

G. -seq, D. Koscielny, K. Hughes, D. Megy, D. Wilson et al., Improving Mosquito Genome Annotation using RNA

L. La-métagénomique, F. Siegwald, C. Texier, and .. .. Hubans-pierlot, Importance des Banques de Séquences pour

;. C. Rna-seq-without-a-reference-genome, D. Carpentier, J. Charif, V. Kielbassa, M. Lacroix et al., Comparison of the Mapping and the Assembly Approaches M

S. Cezard, D. Mctaggart, M. Allen, U. Thomsom, M. Trivedi et al., Exploration of Host Immune Response to Pathogen through an Analysis of Gene Expression T

N. Ema--a-r-package-for-easy-microarray-data-analysis, E. Servant, P. Gravier, C. Gestraud, C. Laurent et al.,

P. Barillot and . .. Hupé, 365 A Fast ab initio Method for Predicting miRNA Precursors in Genomes S

Z. Saci, C. Chen, M. Wéry, M. Silvain, A. Morillon et al., Characterizing Novel Non-Coding Transcripts in Eukaryotic Genomes Using RNA-Seq Data M. Descrimes, p.367

A. Ott, A. Idali, A. Marchais, D. Gautheret, and .. .. , Screening Bacterial Regulatory RNAs and their Targets Using Evolutionary Profiles

C. -seq-data, C. Toffano-nioche, N. Kuchly, P. Nguyen, D. Bouloc et al., Annotation of Non-Coding RNA in Vibrio Using RNA

J. Pele, J. Becu, H. Abdi, and M. .. Chabbert, Bios2mds -an R Package for Metric Multidimensional Scaling Analysis of Multiple Sequence Alignments

, Mixing Biological Descriptors for High Throughput Metalloproteins Prediction in

T. Touzain, S. Mozzanino, M. Schbath, and . .. Petit, Fine-Tuning Motif Detection Among Chip on Chip DNA Fragments F

D. E. Da-silva-figueiredo-celestino, P. Barreto-gomes, and . .. Pascutti, Interaction Profile of Small Inhibitors Complexed with Falcipain-2 and Falcipain-3 Plasmodial Cysteine Proteases P

M. Gautier, F. Molina, F. De-lamotte, and M. .. Ruiz, A Structure-based Classification of the Plant Non-specific Lipid Transfer Protein Superfamily Towards its Functional Characterization C. Fleury

. Bce), . Rmn, J. Et-dynamique-moléculaire, M. Cognet, G. Baouendi et al., Biopolymer Chain Elasticity

M. Protein-peptide-haddocking, A. Trellet, A. Melquiond, and . .. Bonvin,

T. Plasticity, G. Tgf-beta-signaling, G. Cellière, D. Fengos, and .. .. Iber,

A. Talvas, C. Delamarche, and M. E. , 378 Modeling gamma-Cytokine Signalisation from Molecule to Cell P, Meta-Prediction of Amyloidogenic Fragments Using Logistic Regression

C. Human, C. Lipid-metabolism, C. Bettembourg, O. Diot, and . .. Dameron, Cross-Species Metabolic Pathways Comparison -Focus on Mouse

M. Vandenbogaert, O. Jardin-mathe, J. Bigeard, D. Pflieger, and B. .. Schwikowski, FragMixer: A Modular Framework for (Phospho)peptide Identification from Multiple MS/MS Fragmentation Modes V. Hourdel, p.381

;. Patho-genes.org, D. Gardès, R. Bachar, and . .. Christen, 382 YeastIP: a Database for Identification and Phylogeny of Hemiascomycetous Yeasts S. Weiss, F. Samson, Collecte et Analyse des Amorces de PCR Utilisées pour la Détection des Micro-organismes Pathogènes

. Imgt/highv,

E. Alamyar, V. Giudicelli, P. Duroux, and M. .. Lefranc, 384 MODIM : Model-Driven Data Integration for Mining B. Ndiaye, E. Bresso, M. Smaïl-Tabbone, M. Souchet and M

D. Luu, N. Nguyen, J. Muller, L. Moulinier, and O. .. Poch, SM2PH-kb: Data Warehouse Intelligence for the Integrated Study of Human Structural Mutation to Phenotypes Relationships T

E. Biot, J. Burguet, and P. .. Andrey, Eoulsan: a Cloud Computing-Based' Framework Facilitating High Throughput Sequencing Analyses L. Jourdren, M. Bernard, M.-A. Dillies and

C. Renabi-grisbi--infrastructure-distribuée-pour-la-bioinformatique, C. Blanchet, C. Gauthey, O. Caron, S. Collin et al., , p.389

P. .. Index-des-contributeurs--a--abad,

A. S. ,

H. .. Abdi,

A. .. ,

G. .. Achaz,

M. .. Agbessi,

M. .. Agier, , vol.293, p.327

E. .. Alamyar,

M. .. Alaux, , vol.119, p.217

F. .. Alfama-depauw,

D. .. Allen,

J. .. Amselem,

A. .. Anand,

J. .. Andreani, , vol.7, p.23

P. .. Andrey,

M. .. Arguel,

S. .. Aridhi,

A. .. Arneodo,

S. .. Arnoux, , vol.115, p.119

F. .. Artiguenave,

R. .. Assar,

B. .. Asselain,

A. J. ,

B. .. Audit,

J. .. Azé,

G. .. Bader,

A. .. Baillif,

A. .. Baker,

B. .. Ballester,

M. .. Baouendi,

A. .. Bar-hen,

P. .. Bardou,

E. .. Barillot, iii, vii, I, 39, 41, vol.223, p.365

F. .. Barloy-hubler, , vol.309, p.315

D. .. Baron,

G. .. Baronian,

R. .. Barriot,

A. .. Barré,

J. .. Becu,

K. .. Belkhir,

J. .. Bellay,

B. .. Bely,

Y. .. Berchi,

A. .. Bernard,

M. .. Bernard, , vol.83, p.388

V. .. Berry,

C. .. Berthelot,

J. .. Berthelot,

G. .. Bertho,

F. .. Bertucci,

C. .. Bettembourg,

C. .. Bicep,

G. .. Bidaut, , p.323

C. .. Biernacki,

J. .. Bigeard,

T. .. Bigot,

A. .. Bihouée,

E. .. Biot,

E. .. Birmelé, , vol.53, p.307

D. .. Birnbaum,

A. .. Bisch,

T. .. Bitard-feildel,

A. .. Biton,

C. .. Blanchet, , vol.277, pp.389-391

M. .. Blanchette,

M. .. Blaxter,

K. .. Bleakley,

A. .. Blondel, , vol.273, p.275

F. .. Blondin,

Y. .. Blum,

P. .. Bochet,

V. .. Boeva,

A. .. Bonvin,

A. .. Bornot,

B. .. Bost,

P. .. Bouloc,

T. .. Bourquard,

B. .. Boussau,

G. .. Bouvier,

M. .. Bouzayen, , vol.87

M. .. Bouzidi,

M. .. Bras,

B. .. Brault,

L. .. Brehelin, , vol.89, p.193

E. .. Bresso,

A. .. Bretaudeau,

L. .. Brigitte,

L. .. Brillet,

I. .. Brito,

C. .. Brochier-armanet,

G. .. Bronner,

S. .. Brouillet,

G. .. Brown,

C. .. Bruand,

M. .. Brudno,

C. .. Brun,

J. .. Buratti,

G. .. Burger,

J. .. Burguet,

J. .. Busset,

V. .. Cahais,

R. .. Cahuzac,

J. .. Camadro,

A. .. Campan-fournier,

C. .. Canlet,

D. .. Capela,

E. .. Carlinet,

C. .. Caron, , vol.354, p.389

M. .. Carpentier,

M. .. Carpentier,

W. .. Carre,

S. .. Casaregola,

B. .. Caudron,

G. .. Cellière,

T. .. Cezard,

J. .. Chabalier,

M. .. Chabbert,

B. .. Chane-woon-ming,

C. .. Chapple,

D. .. Charif,

E. .. Chautard,

C. .. Chen, , vol.49, p.367

K. .. Chennen,

F. .. Chevenet,

Y. .. Chiari,

A. .. Chifolleau,

M. .. Chlioui,

N. .. Choisne,

J. .. Chomilier,

F. .. Choulet,

R. .. Christen,

P. .. Ciron,

J. .. Coffin,

J. .. Cognet,

O. .. Collin,

E. .. Corre, , vol.215, p.354

O. .. Coullet,

A. .. Criscuolo, , vol.145, p.197

M. .. Cros,

. L. D'orazio,

C. .. Da-silva,

P. .. Da-silva-figueiredo-celestino, , p.373

O. .. Dameron,

E. .. Danchin,

C. .. Danelski,

C. .. Dantec,

E. .. Darbo,

V. .. Daubin,

J. .. Daudin,

C. .. Dauga,

V. .. De-berardinis,

A. .. De-brevern, , vol.25, p.269

L. .. De-koning,

F. .. De-lamotte,

A. .. De-monte,

D. .. Debroas,

C. .. Decraene,

P. .. Dehoux,

S. .. Déjean,

C. .. Delamarche,

O. .. Delattre, , p.223

S. .. Delmotte,

C. .. Deltel,

O. .. Demeure,

P. .. Derreumaux,

M. .. Descrimes,

C. .. Desert,

J. .. Desvignes,

C. .. Devauchelle,

F. .. Devaux,

M. .. Devignes,

C. .. Dhaenens,

W. .. Dhifli,

M. .. Dillies, , vol.358, p.388

C. .. Diot,

D. Entfellner and J. .. , , p.191

E. .. Dubois, , p.335

T. .. Dubois, , vol.39, p.325

N. .. Duclert-savatier,

T. .. Duigou,

F. .. Dumond,

E. .. Duprat,

L. .. Duquenne,

P. .. Durand,

M. .. Durot,

P. .. Duroux,

P. .. Durrens,

J. .. Elsen,

M. .. Emily,

F. .. Enault,

D. .. Enry-barreto-gomes,

J. .. Esque,

J. .. Estellon,

C. .. Etchebest, , vol.261, p.269

G. .. Even,

N. .. Evrard-todeschi,

G. .. Faure, , vol.7, p.23

A. .. Fayyaz-movaghar,

G. .. Fengos,

C. .. Feuillet,

G. .. Fichant,

O. .. Filangi,

S. .. Finet,

P. .. Finetti, , p.323

N. .. Fiorini,

C. .. Fleury,

D. .. Fleury,

P. .. Flicek,

T. .. Flutre,

M. .. Fontecave,

P. .. Forterre,

P. .. Frasse, , vol.87

A. .. Friedrich,

C. .. Froidevaux, ,. I--g--galtier, and N. .. ,

P. .. Gamas,

A. .. Garcia,

M. .. Garcia,

L. .. Garczarek,

J. .. Gardès,

J. .. Garnier,

O. .. Gascuel, , vol.191, p.193

C. .. Gaspin,

D. .. Gautheret, , pp.367-369

C. .. Gauthey, , vol.389, p.391

M. .. Gautier,

P. .. Gayral,

J. .. Gelly, , vol.25, p.263

C. .. Genthon,

G. Pascutti and P. .. ,

P. .. Gestraud,

J. .. Gibrat, , vol.265, p.283

M. .. Giraud,

V. .. Giudicelli,

A. .. Goldar,

I. .. González,

V. .. Gopalan,

D. .. Goudenège, , vol.215, p.309

C. .. Goudot,

M. .. Gouy, , vol.351, p.352

J. .. Gouzy,

S. .. Granjeaud,

G. .. Grasseau,

E. .. Gravier,

S. .. Gribaldo,

A. .. Groppi,

M. .. Groussin,

R. .. Guérois, , vol.7, p.23

G. .. Guilbaud,

N. .. Guilhot,

S. .. Guillaume,

A. .. Guille,

M. .. Guinot,

R. .. Guivarch,

J. .. Hamon,

S. .. Han,

B. .. Hanczar,

E. .. Hantz,

J. .. Haw-king-chon,

M. .. Hellmuth,

M. .. Hernandez-rosales,

C. .. Herrmann,

C. .. Hervé-du-penhoat,

E. .. Hirchaud,

M. .. Hoebeke,

R. .. Houlgatte,

V. .. Hourdel,

C. .. Hubans-pierlot,

D. .. Hughes, , vol.357, p.361

P. .. Hupé, , vol.360, p.365

Y. .. Huyen,

O. .. Hyrien,

A. .. Idali,

A. .. Iltis,

O. .. Inizan, , vol.119, p.217

T. .. Itoh,

M. .. Jacquemot,

J. .. Jacques, , vol.207, p.337

P. .. Jacques,

V. .. Jallu,

V. .. Jamilloux, , vol.115, p.119

J. S. ,

I. .. Janoueix-lerosey,

O. .. Jardin-mathe,

J. .. Jestin,

J. .. ,

L. .. Jones,

A. .. Joseph,

J. L. ,

L. .. Jourdren, , vol.83, p.388

L. .. Journot,

G. .. Jules-clément,

P. .. Jung,

M. .. Kearney,

A. .. Kel,

O. .. Kel,

A. .. Keliet,

G. .. Kerbellec,

P. .. Kersey, , vol.357, p.361

J. .. Kielbassa,

P. .. Kim,

T. .. Kim,

E. .. Kimmel,

E. .. Klipp,

C. .. Klopp, , vol.87

G. .. Koscielny, , vol.357, p.361

M. .. Koskas,

J. .. Kreplak,

E. .. Krin,

C. .. Kuchly,

I. .. Kuperstein,

C. .. Kutter,

K. .. Labadie,

B. .. Labrador,

V. .. Lacroix,

S. .. Lagarrigue,

E. .. Laine,

M. .. Lajoie,

N. .. Lapalu,

M. .. Laporte,

S. .. Larroudé,

N. .. Lartillot, , vol.201, p.209

K. .. Laud-duval,

G. .. Launay,

C. .. Laurent,

D. .. Lavenier,

D. .. Lawson, , vol.357, p.361

L. Bouc and Y. .. ,

L. Cao and K. .. ,

G. .. Le-corguillé,

S. .. Le-crom, , vol.83, p.388

L. Garrec and J. .. ,

F. .. Le-roux,

L. Roy and P. .. ,

E. .. Le-rumeur,

M. .. Lebrun,

F. .. Lecerf,

P. .. Lechat, , vol.135, p.213

V. .. Leclère,

T. .. Lecuit,

B. .. Lee,

V. .. Lefort,

M. .. Lefranc,

F. .. Legeai,

F. .. Lejeune,

F. .. Lejeune,

G. .. Lelandais,

G. .. Lepère,

P. .. Leroy,

T. .. Libourel,

Y. .. Lin,

T. .. Little,

S. .. Liva,

C. .. Loomis,

P. .. López-garcia,

C. .. Lucchetti-miganeh, , vol.309, p.315

W. .. Luscap,

T. .. Luu,

I. .. Luyten,

F. .. Maldarelli,

T. .. Malliavin, , vol.271, p.277

J. .. Mandel,

A. .. Mantsyzov,

A. .. Marchais,

F. .. Mareuil,

M. .. Mariadassou,

J. .. Mariette,

A. .. Marshall,

N. .. Marteu,

L. .. Martignetti,

J. .. Martin,

M. .. Martin,

T. .. Martin, , vol.389, p.391

C. .. Martinez-jimenez,

P. .. Martre, , vol.293, p.327

B. .. Marty,

J. .. Maupetit, , vol.5, p.339

F. .. Maurier,

D. .. Mazel,

G. .. Mazo,

F. .. Mazur,

S. .. Mctaggart,

M. .. Mechref,

C. .. Médigue, , vol.215, p.227

A. .. Mégret,

K. .. Megy, , vol.357, p.361

A. .. Meil,

S. .. Meilhac,

J. .. Melo-ferreira,

A. .. Melquiond,

H. .. Ménager,

E. .. Mephu-nguifo,

C. .. Meslin,

L. .. Mesrob,

D. .. Mestivier,

J. .. Meyniel,

D. .. Meziane-cherif,

M. .. Michaut, , p.253

O. .. Mirabeau,

B. .. Mirauta,

S. .. Missailidis,

F. .. Molina,

J. .. Molina,

D. .. Moreira,

S. .. Moreira,

A. .. Morillon,

I. .. Moszer,

I. .. Mougenot,

L. .. Moulinier,

R. .. Mourad, , p.61

J. .. Moutoussamy,

S. .. Mouysset,

S. .. Mouzeyar,

T. .. Mozzanino,

M. .. Muffato,

J. .. Muller,

P. .. Munson,

D. .. Naquin,

D. .. Navarro,

L. .. Navarro,

B. .. Ndiaye,

C. .. Neri,

M. .. Neri,

B. .. Néron,

N. .. Nguyen,

N. .. Nguyen,

A. .. Nicolas,

P. .. Nicolas,

C. .. Niederlender,

M. .. Nilges, , vol.275, p.277

J. .. Noailles,

G. .. Nuel,

S. .. Ollagnier-de-choudens, , p.371

A. .. Ott, , vol.360, p.365

F. .. Paillier,

A. .. Paris,

F. .. Parmentier,

H. .. Parrinello,

F. .. Partensky,

S. .. Parto,

G. .. Pascal,

J. .. Pathmanathan,

J. .. Pele,

V. .. Perduca, , p.61

L. .. Perfus-barbeoch,

G. .. Perrière,

M. .. Petit,

C. .. Petitjean,

F. .. Peysselon,

D. .. Pflieger,

O. .. Poch,

C. .. Pommier,

R. .. Poujol,

P. .. Poulain,

P. .. Poullet,

A. .. Poupon,

N. .. Prudhomme,

M. .. Pupin,

H. .. Quesneville, , vol.115, p.217

E. .. Quevillon,

C. .. Ragni,

G. .. Ramstein,

V. .. Ranwez,

A. .. Rappailles,

C. .. Ravel, , vol.293, p.327

S. .. Reboux, , vol.119, p.217

F. .. Rechenmann,

C. .. Reisser,

F. .. Reyal,

S. .. Ricard-blum,

H. .. Richard,

M. .. Rieu,

G. .. Rigaill,

D. .. Ritchie,

C. .. Rizzon,

S. .. Robin,

B. .. Robisson,

E. .. Rocha, , vol.107, p.169

R. N. ,

R. F. ,

H. .. Roest-crollius,

T. .. Rose,

M. .. Rosso,

A. .. Roult, , vol.389, p.391

C. .. Rousseau, , vol.87

B. .. Roux,

M. .. Roux,

O. .. Rovellotti,

F. .. Rügheimer,

D. .. Ruiz,

M. .. Ruiz,

Z. .. Saci,

M. .. Sagot, , p.363

A. .. Sahl,

R. .. Saidi,

H. .. Sakai,

A. .. Saladin,

M. .. Salanoubat,

G. .. Salbert,

E. .. Sallet,

O. .. Sallou,

R. .. Salza,

V. .. Sam,

F. .. Samson, , vol.383, p.389

G. .. Santini,

L. .. Sauviac,

F. .. Savagner,

J. .. Schacherer,

S. .. Schbath, , vol.53, p.372

T. .. Schiex,

D. .. Schmidt,

P. .. Schwalie,

B. .. Schwikowski, , vol.295, p.381

B. .. Segurens,

E. .. Selwa,

N. .. Servant,

D. .. Severac,

Y. .. Shen,

D. .. Sherman,

R. .. Shrager,

S. .. Sidibe-bocs,

L. .. Siegwald,

M. .. Silvain,

C. .. Sinoquet, , p.61

F. .. Skouri-panet,

M. .. Smaïl-tabbone,

L. .. Soler,

E. .. Souche,

M. .. Souchet,

C. .. Soulé,

B. .. Spataro,

N. .. Srinivasan,

P. .. Stadler, , vol.181, p.199

O. .. Stahl, , p.323

E. .. Stanley,

.. .. Statomique-consortium,

M. .. Steenman,

D. .. Steinbach,

D. .. Stratmann, , vol.245, p.366

C. .. Tai,

I. .. Talianidis,

A. .. Talvas,

B. .. Tamarit,

T. .. Tanaka,

S. .. Teichmann,

S. .. Tempel, , p.366

N. .. Terrapon,

R. .. Teusan,

F. .. Texier,

J. .. Thalabard,

S. .. Theil,

C. .. Thermes, , vol.49, p.367

D. .. Thieffry,

N. .. Thierry-mieg,

M. .. Thomsom,

D. .. Thybert,

F. .. Tirode,

C. .. Toffano-nioche,

, Tomato Genome Sequencing Consortium, vol.87

F. .. Touzain,

H. .. Touzet, , p.333

M. .. Trellet,

U. .. Trivedi,

S. .. Troncale,

J. .. Trosset,

G. .. Tsagkogeorga,

G. .. Tucker,

P. .. Tuffery, , vol.5, p.339

M. .. Turcotte,

J. .. Van-helden,

M. .. Vandenbogaert,

Y. .. Vandenbrouck,

A. .. Vanvlassenbroeck,

J. .. Varré,

F. .. Vavre,

C. .. Vens,

P. .. Vera-licona,

J. .. Vert, , vol.223, p.311

A. .. Viari,

. S. Vieira-silva,

A. .. Vigneron,

J. .. Vincent and X. .. .-;-w--wang, , vol.293

B. .. Wathelet,

S. .. Watt,

M. .. Weiman,

S. .. Weiss,

M. .. Wéry,

J. .. Whalley,

N. .. Wieseke,

D. .. Wilson, , vol.357, p.361

M. .. Wilson,

A. .. Yu,

B. .. Zeitouni,

A. .. Zinovyev, , vol.41, p.223

A. .. Zoubai,

M. .. Zouine, , vol.87