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sg:publications
2019
[1]
Ambroise, C., Dehman, A., Neuvial, P., Rigaill, G. & Vialaneix, N. Adjacency-constrained hierarchical clustering of a band similarity matrix with application to Genomics. Algorithms for Molecular Biology, 14:22, BioMed Central, 2019. implementation
[2]
Bussy, S., Veil, R., Looten, V., Burgun, A., Gaiffas, S., Guilloux, A., Ranque, B. & Jannot, A.S. Comparison of methods for early-readmission prediction in a high-dimensional heterogeneous covariates and time-to-event outcome framework. BMC Medical Research Methodology, 19(1):50, BioMed Central, 2019. implementation
[3]
Palomares, M.A., Dalmasso, C., Bonnet, E., Derbois, C., Brohard-Julien, S., Ambroise, C., Battail, C., Deleuze, J.F. & Olaso, R.E. Systematic analysis of TruSeq, SMARTer and SMARTer Ultra-Low RNA-seq kits for standard, low and ultra-low quantity samples.. Scientific Reports, Nature Publishing Group, 2019. implementation
[4]
Lannes, R., Rizzon, C. & Lerat, E. Does the Presence of Transposable Elements Impact the Epigenetic Environment of Human Duplicated Genes?. Genes, 10(3):249, MDPI, 2019. implementation
[5]
[6]
Huet, S. & Taupin, M.L. Metamodel construction for sensitivity analysis. , 2019., (working paper or preprint). implementation
[7]
Laso-Jadart, R., Sugier, K., Petit, E., Labadie, K., Peterlongo, P., Ambroise, C., Wincker, P., JAMET, J.L. & Madoui, M.A. Linking Allele-Specific Expression And Natural Selection In Wild Populations. , 2019., (working paper or preprint). implementation
[8]
2018
[9]
Billat, V., Brunel, N.J.B., Carbillet, T., Labbe, S. & Samson, A. Humans are able to self-paced constant running accelerations until exhaustion. Physica A: Statistical Mechanics and its Applications, 506:290-304, Elsevier, 2018. implementation
[10]
Guinot, F., Szafranski, M., Ambroise, C. & Samson, F. Learning the optimal scale for GWAS through hierarchical SNP aggregation. BMC Bioinformatics, 19(1):459, BioMed Central, 2018. implementation
[11]
Jonchere, V., Marisa, L., Greene, M., Virouleau, A., Buhard, O., Bertrand, R., Svrcek, M., Cervera, P., Goloudina, A., Guillerm, E., Coulet, F., Landman, S., Ratovomanana, T., Job, S., Ayadi, M., Elarouci, N., Armenoult, L., Merabtene, F., Dumont, S., Parc, Y., Lefevre, J., Andre, T., Flejou, J.F., Guilloux, A., Collura, A., De Reynies, A. & Duval, A. Identification of Positively and Negatively Selected Driver Gene Mutations Associated With Colorectal Cancer With Microsatellite Instability Positive Selection Pressure Mutational Background Negative Selection Pressure Mutational Frequency Microsatellite length (bp). Cellular and Molecular Gastroenterology and Hepatology, 6(3):277-300, Philadelphia, PA : American Gastroenterological Association, [2015]-, 2018. implementation
[12]
Brunel, N., Goujot, D., Labarthe, S. & Laroche, B. Parameter estimation for dynamical systems using an FDA approach. In 11th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2018), 2018. implementation
[13]
Brunel, N., Goujot, D., Labarthe, S. & Laroche, B. Parameter estimation for dynamical systems using an FDA approach. In 11th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2018), 2018. implementation
[14]
Laroche, B., Brunel, N., Goujot, D. & Labarthe, S. Parameter estimation for dynamical systems using an FDA approach. In International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2018), pages np, 2018. implementation
[15]
[16]
Robin, G., Ambroise, C. & Robin, S.S. Incomplete graphical model inference via latent tree aggregation. , 2018., (working paper or preprint). implementation
[17]
Alaya, M.Z., Lemler, S., Guilloux, A. & Allart, T. High-dimensional time-varying Aalen and Cox models. , 2018., (working paper or preprint). implementation
[18]
Virouleau, A., Guilloux, A., Gaiffas, S. & Bogdan, M. HIGH-DIMENSIONAL ROBUST REGRESSION AND OUTLIERS DETECTION WITH SLOPE. , 2018., (working paper or preprint). implementation
2017
[19] (Theses)
[20]
Stanislas, V., Dalmasso, C. & Ambroise, C. Eigen-Epistasis for detecting Gene-Gene interactions. BMC Bioinformatics, 18:54, BioMed Central, 2017. implementation
[21]
Stanislas, V., Dalmasso, C. & Ambroise, C. Eigen-Epistasis for detecting gene-gene interactions. BMC Bioinformatics, 18:np, BioMed Central, 2017. implementation
[22]
Sadacca, B., Hamy-Petit, A.S., Laurent, C., Gestraud, P., Bonsang-Kitzis, H., Pinheiro, A., Abecassis, J., Neuvial, P. & Reyal, F. New insight for pharmacogenomics studies from the transcriptional analysis of two large-scale cancer cell line panels. Scientific Reports, 7(1):15126, Nature Publishing Group, 2017. implementation
[23]
Becu, J.M., Grandvalet, Y., Ambroise, C. & Dalmasso, C. Beyond support in two-stage variable selection. Statistics and Computing, 27(1):169-179, Springer Verlag (Germany), 2017. implementation
[24]
Alaya, M.Z., Bussy, S., Gaiffas, S. & Guilloux, A. Binarsity: a penalization for one-hot encoded features. , 2017., (working paper or preprint). implementation
[25]
Bussy, S., Guilloux, A., Gaiffas, S. & Jannot, A.S. C-mix: a high dimensional mixture model for censored durations, with applications to genetic data. , 2017., (working paper or preprint). implementation
[26]
Tabouy, T., BARBILLON, P. & Chiquet, J. Variational Inference for Stochastic Block Models from Sampled Data. , 2017., (working paper or preprint). implementation
[27]
Champion, M., Chiquet, J., Neuvial, P., Elati, M. & Birmele, E.E. Identification of deregulated transcription factors involved in subtypes of cancers. , 2017., (working paper or preprint). implementation
2016
[28] (Theses)
[29] (Theses)
[30]
Guilloux, A., Lemler, S. & Taupin, M.L. Adaptive estimation of the baseline hazard function in the Cox model by model selection, with high-dimensional covariates. Journal of Statistical Planning and Inference, 171:38-62, Elsevier, 2016. implementation
[31]
Guilloux, A., Lemler, S. & Taupin, M.L. Adaptive kernel estimation of the baseline function in the Cox model with high-dimensional covariates. Journal of Multivariate Analysis, 148:141-159, Elsevier, 2016. implementation
[32]
Brouard, C., Szafranski, M. & d'Alche-Buc, F. Input output kernel regression: Supervised and semi-supervised structured output prediction with operator-valued kernels . Journal of Machine Learning Research, 17:(elec. proc.), Microtome Publishing, 2016. implementation
[33]
Carapito, R., Jung, N., Kwemou, M., Untrau, M., Michel, S., Pichot, A., Giacometti, G., Macquin, C., Ilias, W., Morlon, A., Kotova, I., Apostolova, P., Schmitt-Graeff, A., Cesbron, A., Gagne, K., Oudshoorn, M., van der Holt, B., Labalette, M., Spierings, E., Picard, C., Loiseau, P., Tamouza, R., Toubert, A., Parissiadis, A., Dubois, V., Lafarge, X., Maumy-Bertrand, M., Bertrand, F., Vago, L., Ciceri, F., Paillard, C., Querol, S., Sierra, J., Fleischhauer, K., Nagler, A., Labopin, M., Inoko, H., von dem Borne, P., Kuball, J.H.E., Ota, M., Katsuyama, Y., Michallet, M., Lioure, B., Peffault De Latour, R., Blaise, D., Cornelissen, J.J., Yakoub-Agha, I., Claas, F., Moreau, P., Milpied, N., Charron, D., Mohty, M., Zeiser, R., Socie, G. & Bahram, S. Matching for the non-conventional MHC-I MICA gene significantly reduces the incidence of acute and chronic GVHD. Blood, American Society of Hematology, 2016. implementation
[34]
Kwemou, M. Non-asymptotic oracle inequalities for the Lasso and Group Lasso in high dimensional logistic model. ESAIM: Probability and Statistics, 20:309-331, EDP Sciences, 2016. implementation
[35]
Vacher, C., Tamaddoni-Nezhad, A., Kamenova, S., Dubois Peyrard, N., Moalic, Y., Sabbadin, R., SCHWALLER, L., Chiquet, J., Alex Smith, M., Vallance, J., Fievet, V., Jakuschkin, B. & BOHAN, D.A. Learning ecological networks from next-generation sequencing data. In Ecosystem Services: From Biodiversity to Society, Part 2, 54:np, 2016. implementation
[36]
[37]
[38]
Celisse, A., Marot, G., Pierre-Jean, M. & Rigaill, G. New efficient algorithms for multiple change-point detection with kernels. , 2016., (working paper or preprint). implementation
2015
[39]
[40] (Theses)
[41]
Chevalier, E., Vath, V.L., Roch, A. & Scotti, S. Optimal exit strategies for investment projects. Journal of Mathematical Analysis and Applications, 425(2):666-694, Elsevier, 2015.
[42]
Picchetti, T., Chiquet, J., Elati, M., Neuvial, P., Nicolle, R. & Birmele, E.E. A model for gene deregulation detection using expression data. BMC Systems Biology, BioMed Central, 2015. implementation
[43]
Pierre-Jean, M., Rigaill, G. & Neuvial, P. Performance evaluation of DNA copy number segmentation methods. Briefings in Bioinformatics, 16(4), Oxford University Press (OUP), 2015. implementation
[44]
Dehman, A., Ambroise, C. & Neuvial, P. Performance of a blockwise approach in variable selection using linkage disequilibrium information. BMC Bioinformatics, pages 14, BioMed Central, 2015. implementation
[45]
Dalmasso, C., Carpentier, W., Guettier, C., Camilleri-Broet, S., Vendramini Borelli, W., Campos dos Santos, C.R., Castaing, D., Duclos-Vallee, J.C. & Broet, P. Patterns of chromosomal copy-number alterations in intrahepatic cholangiocarcinoma. BMC Cancer, 15:126, BioMed Central, 2015. implementation
[46]
Latouche, P., Birmele, E. & Ambroise, C. Handbook of Mixed Membership Models and Their Applications. , pages 547-568Chapman and Hall, 2015.
[47]
Becu, J.M., Grandvalet, Y., Ambroise, C. & Dalmasso, C. Significance testing for variable selection in high-dimension. In Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), pages 1-8, IEEE, 2015. implementation
[48]
[49]
[50]
[51]
Becu, J.M., Grandvalet, Y., Ambroise, C. & Dalmasso, C. Beyond Support in Two-Stage Variable Selection. , 2015., (working paper or preprint). implementation
[52]
[53]
Kwemou, M., Taupin, M.L. & Tocquet, A.S. MODEL SELECTION IN LOGISTIC REGRESSION. , 2015., (working paper or preprint). implementation
[54]
[55]
[56]
Brouard, C., d'Alche-Buc, F. & Szafranski, M. Input Output Kernel Regression. , 2015., (working paper or preprint). implementation
2014
[57] (Theses)
[58] (Theses)
[59]
Latouche, P., Birmele, E. & Ambroise, C. Model Selection in Overlapping Stochastic Block Models. Electronic Journal of Statistics, 8:762-794, 2014.
[60]
Dedecker, J., Samson, A. & Taupin, M.L. Estimation in autoregressive model with measurement error. ESAIM Probab. \& Stat., 18():277-307, 2014., (http://dx.doi.org/10.1051/ps/2013037). implementation
[61]
Lemler, S. Oracle inequalities for the Lasso in the high-dimensional Aalen multiplicative intensity model. Accepted in Les Annales de l'Institut Henri Poincaré, 00(?), 2014. implementation
[62]
Pierre-Jean, M., Rigaill, G. & Neuvial, P. Performance evaluation of DNA copy number segmentation methods. Briefings in Bioinformatics, 2014. implementation
[63]
Chalhoub, B., Denoeud, F., Liu, S., Parkin, I.A.P., Tang, H., Wang, X., Chiquet, J., Belcram, H., Tong, C., Samans, B., Correa, M., Da Silva, C., Just, J., Falentin, C., Koh, C.S., Le Clainche, I., Bernard, M., Bento, P., Noel, B., Labadie, K., Alberti, A., Charles, M., Arnaud, D., Guo, H., Daviaud, C., Alamery, S., Jabbari, K., Zhao, M., Edger, P.P., Chelaifa-Ammari, H., Tack, D., Lassalle, G., Mestiri, I., Schnel, N., Le Paslier, M.C., Fan, G., Renault, V., Bayer, P.E., Golicz, A.A., Manoli, S., Lee, T.H., Dinh Thi, V.H., chalabi, s., Hu, Q., Fan, C., Tollenaere, R., Lu, Y., Battail, C., Shen, J., Sidebottom, C.H.D., Wang, X., Canaguier, A., Chauveau, A., Berard, A., Deniot, G., Guan, M., Liu, Z., Sun, F., Lim, Y.P., Lyons, E., Town, C.D., Bancroft, I., Wang, X., Meng, J., Ma, J., Pires, J.C., King, G.J., Brunel, D., Delourme, R., Renard, M., Aury, J.M., Adams, K.L., Batley, J., Snowdon, R.J., Tost, J., Edwards, D., Zhou, Y., Hua, W., Sharpe, A.G., Paterson, A.H., Guan, C. & Wincker, P. Early allopolyploid evolution in the post-Neolithic[i] Brassica napus[/i] oilseed genome. Science, 345(6199):950-953, American Association for the Advancement of Science, 2014. implementation
[64]
Hahn, G., Bujan, A.F., Fregnac, Y., Aertsen, A., Kumar, A. & Brunel, N. Communication through Resonance in Spiking Neuronal Networks. PLoS Computational Biology, 10(8):e1003811, Public Library of Science, 2014. implementation
[65]
Jeanmougin, M., Charbonnier, C., Guedj, M. & Chiquet, J. Probabilistic Graphical Models for Genetics, Genomics and Postgenomics. , ():xxx, Oxford University Press, 2014.
[66]
Chazottes, J., Cuny, C., Dedecker, J., Fan, X. & Lemler, S. Limit theorems and inequalities via martingale methods. In ESAIM: Proceedings, 44():177-196, , 2014.
[67]
Laloe, D., Jaffrezic, F., Chiquet, J. & Gaultier, M. FLPCA: a fused-LASSO PCA-based approach to identify footprints of selection in differentiated populations from dense to SNP data: applications to human and cattle data. In Proceedings of the International Biometric Conference, Florence, Italy, ():, , 2014.
[68]
[69]
Brunel, N.J.B. & Clairon, Q. A Tracking Approach to Parameter Estimation in Linear Ordinary Differential Equations. , 2014., (working paper or preprint). implementation
[70]
2013
[71]
Chelaifa, H., Chague, V., Chalabi, S., Mestiri, I., Arnaud, D., Deffains, D., Lu, Y., Belcram, H., Huteau, V., Chiquet, J., Coriton, O., Just, J., Jahier, J. & Chaloub, B. Prevalence of gene expression additivity in genetically stable wheat allohexaploids. New Phytologist, 197(3):730-736, 2013.
[72]
Chevalier, E., Ly Vath, V. & Scotti, S. An optimal dividend and investment control problem under debt constraints. SIAM J. Financial Math., 4(1):297-326, 2013. implementation
[73]
Chiquet, J. & Limnios, N. Stochastic Reliability and Maintenance Modeling. , 9():, Springer, 2013.
[74]
Chiquet, J., Mary-Huard, T. & Robin, S. Multi-trait genomic selection via multivariate regression with structured regularization. In Proceedings of the MLCB NIPS'13 workshop, ():, , 2013.
[75]
Dehman, A., Ambroise, C. & Neuvial, P. Incorporating linkage disequilibrium blocks in Genome-Wide Association Studies. In JOBIM proceeding 2013, ():, , 2013.
[76]
Gutierrez, P., Rigaill, G. & Chiquet, J. A fast homotopy algorithm for a large class of weighted classification problems. In Proceedings of the MLCB NIPS'13 workshop, South lake Thao, ():, , 2013.
[77]
[78]
[79]
Pierre-Jean, M. Change-point detection with kernel methods : application to DNA copy number signals. , 2013., (45e Journées de Statistiques de la SFDS , Toulouse).
[80]
2012
[81] (Theses)
[82]
Acuna, V., Birmele, E., Cottret, L., Crescenzi, P., Jourdan, F., Lacroix, V., Marchetti-Spaccamela, A., Marinov, A., Vieira Milreu, P., Sagot, M.F. & Stougie, L. Telling Stories: Enumerating maximal directed acyclic graphs with a constrained set of sources and targets. Theoretical Computer Science, 457(2):1-9, 2012.
[83]
Ambroise, C. & Matias, C. New consistent and asymptotically normal parameter estimates for random graph mixture models. Journal of the Royal Statistical Society: Series B, 74(1):3-35, 2012. implementation
[84]
Bouaziz, M., Paccard, C., Guedj, M. & Ambroise, C. SHIPS: Spectral Hierarchical Clustering for the Inference of Population Structure in Genetic Studies. PloS One, 7(10):e45685, 2012.
[85]
Chiquet, J., Grandvalet, Y. & Charbonnier, C. Sparsity with sign-coherent groups of variables via the cooperative-Lasso. The Annals of Applied Statistics, 6(2):795-830, 2012. implementation
[86]
Didier, G., Corel, E., Laprevotte, I., Grossmann, A. & Devauchelle, C. Variable length local decoding and alignment-free sequence comparison. Theoretical Computer Science, 462():1-11, 2012. implementation
[87]
Dillies, M., Rau, A., Aubert, J., Hennequet-Antier, C., Jeanmougin, M. & Servant, N. A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis. Briefings in Bioinformatics, xx():, 2012. implementation
[88]
Guergnon, J., Dalmasso, C., Broet, P., Meyer, L., Westrop, S., Imami, N., Vicenzi, E., Morsica, G., Tinelli, M., Poma, B., Goujard, C., Potard, V., Gotch, F., Casoli, C., Cossarizza, A. & others, O. Single Nucleotide Polymorphism-defined Class-I and Class-III MHC genetic subregions contribute to natural long-term non progression in HIV infection. Journal of Infectious Diseases, 205(5):718-24, 2012.
[89]
Latouche, P., Birmele, E. & Ambroise, C. Variational Bayesian Inference and Complexity Control for Stochastic Block Models. Statistical Modelling, 12(1):93-115, 2012. implementation
[90]
Prum, B. Chaînes de Markov et absorption ; application à l'algorithme de Fu en génomique. J. Société Française de Statistique, 152 n°2():37-51, 2012.
[91]
Bouaziz, M., Jeanmougin, M. & Guedj, M. Multiple-testing in large-scale genetic studies. , ():, Bonin A, Pompanon F eds, Methods in Molecular Biology Series, Humana Press., 2012.
[92]
[93]
[94]
[95]
[96]
Lim, T., y, , Sahut, J.M. & Scotti, S. Bid-ask spread modelling, a perturbation approach. , 2012.
[97]
Pierre-Jean, M. Segmentation de données génomiques en cancérologie. , 2012., (Journée annuelle du groupe Biopharmacie et Santé de la SFDS).
2011
[98]
[99]
Bouaziz, M., Ambroise, C. & Guedj, M. Accounting for Population Stratification in Practice: a Comparison of the Main Strategies Dedicated to Genome-Wide Association Studies. PLOS one, 6(12):, 2011. implementation
[100]
Broet, P., Dalmasso, C., Tan, E., Alifano, M., Zhang, S., Wu, J., Lee, M., Regnard, J., Lim, W., Koong, H., Agasthian, T., Miller, L., Camilleri-Broet, S. & Tan, P. Genomic Profiles Specific to Patient Ethnicity in Lung Adenocarcinoma. Clinical Cancer Research, 17(11):3542-50, 2011.
[101]
Chiquet, J., Grandvalet, Y. & Ambroise, C. Inferring Multiple Graphical Structures. Statistics and Computing, 21(4):537-553, 2011. implementation
[102]
Dalmasso, C. & Broet, P. Detection of chromosomal abnormalities using high resolution arrays in clinical cancer research. Journal of Biomedical Informatics, (doi:10.1016/j.jbi.2011.06.003):, 2011. implementation
[103]
Jeanmougin, M., Guedj, M. & Ambroise, C. Defining a robust biological prior from Pathway Analysis to drive Network Inference.. J-SFdS, 152(2):, 2011. implementation
[104]
Latouche, P., Birmele, E. & Ambroise, C. Overlapping Stochastic Block Models with Application to the French Political Blogosphere. Annals of Applied Statistics, 5(1):309-336, 2011.
[105]
Chiquet, J., Grandvalet, Y. & Charbonnier, C. Sparsity with sign-coherent groups of variables via the cooperative-Lasso. In Proceedings of SPARS'11, Edimburgh, ():, , 2011.
[106]
Chiquet, J. Réseaux biologiques. , 2011., (La gazette des mathématiciens No. 130 pp. 76--82). implementation
[107]
2010
[108]
Charbonnier, C., Chiquet, J. & Ambroise, C. Weighted-Lasso for Structured Network Inference from Time Course Data. Statistical Applications in Genetics and Molecular Biology, 9(1):, 2010. implementation
[109]
Corel, E., Pitschi, F., Laprevotte, I., Grasseau, G., Didier, G. & Devauchelle, C. MS4 - Multi-Scale Selector of Sequence Signatures: An alignment-free method for classification of biological sequences. BMC Bioinformatics, 11(406):, 2010., (doi:10.1186/1471-2105-11-406). implementation
[110]
Jeanmougin, M., de Reynies, A., Marisa, L., Paccard, C., Nuel, G. & Guedj, M. Should We Abandon the t-Test in the Analysis of Gene Expression Microarray Data: A Comparison of Variance Modeling Strategies. PLoS ONE, 5(9):e12336, 2010. implementation
[111]
Pitschi, F., Devauchelle, C. & Corel, E. Automatic detection of anchor points for multiple sequence alignment. BMC Bioinformatics, 11(445):, 2010. implementation
[112]
Zanghi, H., Picard, F., Miele, V. & Ambroise, C. Strategies for Online Inference of Network Mixture. Annals of Applied Statistics, 4(2):687-714, 2010. implementation
[113]
Zanghi, H., Volant, S. & Ambroise, C. Clustering based on random graph model embedding vertex features. Pattern Recognition Letters, 31(9):830-836, 2010.
[114]
, (eds). La démarche statistique. , (), Cépaduès, 2010.
[115]
Charbonnier, C., Chiquet, J. & Ambroise, C. Weighted-Lasso for Structured Network Inference for Time-Course data. In JOBIM'10, Montpellier, 2010.
[116]
Chiquet, J., Grandvalet, Y. & Ambroise, C. Inferring Multiple Graphical Structures. In Workshop MODGRAPHII, JOBIM'10, Montpellier, 2010.
[117]
Grandvalet, Y., Chiquet, J. & Ambroise, C. Inferring Multiple Regulation Networks. In Proceedings of the MLCB NIPS'10 Workshop, Vancouver, 2010.
[118]
Grandvalet, Y., Chiquet, J. & Ambroise, C. Inférence jointe de la structure de modèles graphiques gaussiens. In actes de CAp'10, Clermont-Ferrand, 2010.
2009
[119]
Ambroise, C., Chiquet, J. & Matias, C. Inferring sparse Gaussian graphical models with latent structure. Electronic Journal of Statistics, 3():205-238, 2009. implementation
[120]
Chiquet, J., Smith, A., Grasseau, G., Matias, C. & Ambroise, C. SIMoNe: Statistical Inference for MOdular NEtworks. Bioinformatics, 25(3):417-418, 2009. implementation
[121]
Durot, C., Lebarbier, E. & Tocquet, A.S. Estimating the joint distribution of independent categorical variables via model selection. Bernoulli, 15(2):475-507, 2009.
[122]
Oudot, T., Lesueur, F., Guedj, M., de Cid, R., McGinn, S., Heath, S., Foglio, M., Prum, B., Lathrop, M., Prud'homme, J. & Fischer, J. An association study of 22 candidate genes in psoriasis families reveals shared genetic factors with other autoimmune and skin disorders. J Invest Dermatol., 129(11):2637-45, 2009.
[123]
Picard, F., Miele, V., Daudin, J.J., Cottret, L. & Robin, S. Deciphering the connectivity structure of biological networks using MixNet. BMC Bioinformatics, 10(Suppl 6):S17, 2009.
[124]
Tian, Z., Rizzon, C., Du, J., Zhu, L., Bennetzen, J., Gaut, B., Jackson, S. & Ma, J. Do genetic recombination and gene density shape the pattern of DNA elimination in rice LTR-retrotransposons?. Genome Res., 19(12):2221-30, 2009. implementation
[125]
Ambroise, C. & Dang, M. Data Analysis. , ():289-318, Wiley, 2009.
[126]
Latouche, P., Birmele, E. & Ambroise, C. Advances in Data Analysis, Data Handling and Business Intelligence. , ():229-239, springer, 2009. implementation
[127]
Chiquet, J., Charbonnier, C. & Ambroise, C. SIMoNe : Statistical Inference of Modular Network. In Workshop MODGRAPH, JOBIM'09, Nantes, 2009.
[128]
Latouche, P., Birmele, E. & Ambroise, C. Uncovering overlapping clusters in biological networks. In Journées ouvertes en biologie, informatique et mathématiques (Jobim). Nantes, 2009.
2008
[129]
Birmele, E., Elati, M., Rouveirol, C. & Ambroise, C. Identification of functional modules based on transcriptional regulation structure. BMC Proceedings, 2((Suppl 4):S4):, 2008.
[130]
Guedj, M., Nuel, G. & Prum, B. A note on allelic tests in case-control association studies. Annals of Human Genetics, 72():407-409, 2008. implementation
[131]
Guedj, M., Bourillon, A., Combadieres, C., Rodero, M., Dieude, P., Descamps, V., Dupin, N., Wolkenstein, P., Aegerter, P., Lebbe, C., Basset-Seguin, N., Prum, B., Saiag, P., Grandchamp, B. & Soufir, N. Variants of the MATP/SLC45A2 gene are protective for melanoma in the French population. Human Mutation, 29():1154-1160, 2008. implementation
[132]
Zanghi, H., Ambroise, C. & Miele, V. Fast Online Graph Clustering via Erdös Renyi Mixture. Pattern Recognition, 41(12):3592-3599, 2008.
2007
[133]
Avalos, M., Grandvalet, Y. & Ambroise, C. Parsimonious additive models. CSDA, 51(6):2851-2870, 2007.
[134]
Didier, G., Debomy, L., Pupin, M., Zhang, M., Grossmann, A., Devauchelle, C. & Laprevotte, I. Comparing sequences without alignments: application to HIV/SIV subtyping. BMC Bioinformatics, 8():1, 2007.
[135]
Garnier, S., Dieude, P., Michou, L., l, , Bardin, T., Prum, B. & Cornelis, F. IRF5 rs2004640-T allele, the new genetic factor for systemic lupus erythematosus, is not associated with rheumatoid arthritis. Ann. Rheum. Dis., 66():828-831, 2007.
[136]
Gaut, B., Wright, S., Rizzon, C., Dvorak, J. & Anderson, L. Recombination: an underappreciated factor in the evolution of plant genomes.. Nat Rev Genet., 8():77-84, 2007.
[137]
Jacq, L., Garnier, S., Dieude, P., Michou, L., l, , Prum, B., Bardin, T. & Cornelis, F. The ITGAV rs3738919-C allele is associated with and linked to rheumatoid arthritis in the European Caucasian population: a family-based study. Arthritis Research \& Therapy, 9(R63):, 2007.
[138]
Michou, L., Lasbleiz, S., l, , Prum, B., Bardin, T., Dieude, P. & Cornelis, F. Linkage proof for PTPN22, the new rheumatoid arthritis susceptibility gene, a human autoimmunity gene. Proc. Natl. Acad. Sci. USA, 104():1649-1654, 2007.
[139]
Same, A., Ambroise, C. & Govaert, G. An online Classification EM algorithm based on the mixture model. Statistics and Computing, 17(3):209-218, 2007.
[140]
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[141]
Corel, E., El Feghali, R., Gerardin, F., Hoebeke, M., Nadal, M., Grossmann, A. & Devauchelle, C. Local Similarities and Clustering of Biological Sequences : New Insights from N-local Decoding. In The First International Symposium on Optimization and Systems Biology (OSB 2007), Lecture Notes in Operations Research(7):189-195, World Publishing, 2007. implementation
[142]
Corel, E., El Feghali, R., Gerardin, F., Hoebeke, M., Nadal, M., Louis, A., Laprevotte, I., Grossmann, A. & Devauchelle, C. Local Similarities and Clustering of Biological Sequences. In Actes de JOBIM 2007, pages 69-71, 2007.
2006
[143]
Anderson, L., Lai, A., Stack, S., Rizzon, C. & Gaut, B. Uneven distribution of expressed sequence tag loci on maize pachytene chromosomes.. Genome Res., 16():115-22, 2006.
[144]
Drouaud, J., Camilleri, C., Bourguignon, P., l, , Prum, B., Quesneville, H. & Mezard, C. Free Full Text Variation in crossing-over rates across chromosome 4 of Arabidopsis thaliana reveals the presence of meiotic recombination “hot spots”.. Genome Research, 16():106-114, 2006.
[145]
Michou, L., Croiseau, P., l, , Prum, B., Clerget, F. & Cornelis, F. Confirmation of the Shared Epitope Allele Classification. Arthritis Research and Therapy, 28():79-, 2006.
[146]
Nicolas, P., Tocquet, A.S., Miele, V. & Muri, F. A Reversible Jump Markov Chain Monte-Carlo Algorithm for Bacterial Promoter Motifs Discovery. Journal of Computational Biology, 13(3):651-667, 2006.
[147]
Rizzon, C., Ponger, L. & Gaut, B. Striking similarities in the genomic distribution of tandemly arrayed genes in Arabidopsis and rice.. PLoS Comput Biol., 2(9):e115, 2006.
[148]
Zhu, X., Ambroise, C. & McLachlan, G. Selection bias in working with the top genes in supervised classification of tissue samples. Statistical Methodology, 3():29-41, 2006.
[149]
Prum, B. & Tocquet, A.S. The use of Markov Models and Hidden Markov Models in genomics. In Mathematical and computational methods in biology, (), Herman, 2006.
[150]
Miele, V., Vaillant, C., D'Aubenton, Y., Robelin, D., Prum, B. & Thermes, C. DNA sequence drives nucleosome occupancy of yeast promoters. In Proceeding of JOBIM, 2006.
[151]
[152]
[153]
2005
[154]
Bekaert, M., Richard, H., Prum, B. & Rousset, J. Identification of programmed translational -1 frameshifting sites in the genome of Saccharomyces cerevisiae. Genome Research, 10():1411-1420, 2005.
[155]
Dieude, P., Garnier, S., Michou, L., l, , Prum, B. & Cornelis, F. Rheumatoid arthritis seropositive for the rheumatoid factor is linked to the protein tyrosine phosphatase nonreceptor 22-620W allele. Arthritis Research \& Therapy, 7():, 2005.
[156]
Tezenas du Montcel, S., Michou, L., l, , Prum, B., Cornelis, F. & Clerget, F. New classification of HLA-DRB1 alleles support the shared epitope hypothesis of rheumatoid arthritis susceptibility. Arthritis Rheumatism, 52(1063-1068):, 2005.
[157]
Weyer-Menkoff, J., Devauchelle, C., Grossmann, A. & Grunewald, S. Integer linear programming as a tool for constructing trees from quartet data. Comput Biol Chem, 29(3):196-203, 2005.
[158]
2004
[159]
Dieude, P., Osorio, J., l, , Prum, B. & Cornelis, F. A TNFR1 genotype with a protective role in familial rheumatoid arthritis.. Arthritis Rheumatism, 50():413-419, 2004.
[160]
Osorio , J., Bukulmez, H., Petit-Teixeira, E., Michou, L., l, , Prum, B., Olson, J. & Cornelis, F. Dense genome-wide linkage analysis of rheumatoid arthritis including covariates. Arthritis Rheumatism, 50():2557-2565, 2004.
[161]
, (eds). Analyzing microarray gene expression data. , (), Wiley, 2004. implementation
[162]
Prum, B., Bourguignon, P., Guedj, M., Kepes, F., Matias, C., Nuel, G. & Omont, N. La recherche de gènes impliqués dans une maladie, collaboration avec Genset-Serono. , 2004., (Matapli 74 p23-41).
2003
[163]
Durot, C. & Tocquet, A.S. On the distance between the empirical process and its concave majorant in a monotone regression framework. Ann. I. H. Poincaré, Probabilités \\& Statistique, 39():217-240, 2003.
[164]
Goldstein, D., Fondrat, C., Muri, F., Nuel, G., Saragueta, P., Tocquet, A.S. & Prum, B. Short inverse complementary amino-acid sequences generate protein complexity. C. R. Acad. Sci. Biologie, 326():339-348, 2003.
[165]
Lerat, E., Rizzon, C. & Biemont, C. Sequence divergence within transposable element families in the Drosophila melanogaster genome.. Genome Res., 13():1889-96, 2003.
[166]
Leuteneger, A., Prum, B., Genin, E., Verny, C., Lemainque, A., Clerget, F. & Thompson, E. Estimation of the inbreeding coefficient through use of genomic data. Am. J. Hum. Genet., 73():516-523, 2003.
[167]
Rizzon, C., Martin, E., Marais, G., Duret, L., Segalat, L. & Biemont, C. Patterns of selection against transposons inferred from the distribution of Tc1, Tc3, and Tc5 insertions in the mut-7 line of the nematode Caenorhabditis elegans.. Genetics, 165():1127-1135, 2003.
2002
[168]
Dieude, P., Petit, E., l, , Prum, B. & Cornelis, F. Association Between Tumor Necrosis Factor Receptor II and Familial, but Not Sporadic, Rheumatoid Arthritis. Arthritis Rheumatism, 46():2039-2044, 2002.
[169]
Nicolas, P., Bize, L., Muri, F., Hoebeke, M., Rodolphe, F., Ehrlich, S., Prum, B. & Bessieres, P. Mining Bacillus Subtilis chromosome heterogeneities using hidden Markov models. Nucleic Acids Research, 30():1418-1426, 2002.
[170]
Rizzon, C., Marais, G., Gouy, M. & Biemont, C. Recombination rate and the distribution of transposable elements in the Drosophila melanogaster genome.. Genome Res., 12():400-407, 2002.
[171]
[172]
2001
[173]
Durot, C. & Tocquet, A.S. Goodness of fit test for isotonic regression. ESAIM, Probabilités \\& Statistique, 5():119-140, 2001.
[174]
Muri, F. & Prum, B. Une approche statistique de l'analyse des génomes. La Gazette des Mathématiciens, 89():63-98, 2001.
[175]
Tocquet, A.S. Likelihood based inference in nonlinear regression models using the p* and R* approach. Scandinavian Journal of Statistics, 28():429-443, 2001.
[176]
[177]
2000
[178]
Goldstein, D., Muri, F., Saragueta, P. & Prum, B. Inverse Complementary homologues of cysteine signatures. CRAS Sciences de la Vie, 323(2):167-172, 2000.
[179]
[180]
1999
[181]
Bize, L., Muri, F., Samson, F., Rodolphe, F., Ehrlich, S., Prum, B. & Bessieres, P. Searching gene transfers on Bacillus Subtilis using hidden Markov models. In Recomb'99 Proceedings of the Third Annual International Conference on Computational Molecular Biology, 1999.
[182]
sg/publications.txt · Last modified: 2016/04/21 14:24 (external edit)

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