{"id":210,"date":"2014-11-24T15:10:07","date_gmt":"2014-11-24T14:10:07","guid":{"rendered":"http:\/\/pageperso.math.univ-toulouse.fr\/maugis\/?page_id=210"},"modified":"2019-06-11T13:56:02","modified_gmt":"2019-06-11T12:56:02","slug":"mixstatseqpubli","status":"publish","type":"page","link":"https:\/\/perso.math.univ-toulouse.fr\/maugis\/mixstatseq\/mixstatseqpubli\/","title":{"rendered":"Publications"},"content":{"rendered":"<ul>\n<li>Mondet, F.,\u00a0<a href=\"http:\/\/andrea-rau.com\" target=\"_blank\">Rau, A.<\/a>, Klopp, C., Rohmer, M. Severac, D., Le Conte, Y., and Alaux, C.(2018). Transcriptome profiling of the honeybee parasite Varroa destructor provides new biological insights into the mite adult life cycle. <em>BMC Genomics<\/em>, 19(1):328.<\/li>\n<li>Celeux, G., Maugis-Rabusseau, C. and Sedki, M. (2018). Variable selection in model-based clustering and discriminant analysis with regularization approach. Accepted\u00a0in <em>Advances in Data Analysis and Classification<\/em>.<br \/>\n<a href=\"https:\/\/tel.archives-ouvertes.fr\/hal-01053784\/document\" target=\"_blank\">[Hal-01053784<\/a>]<\/li>\n<li><a href=\"http:\/\/godichon.perso.math.cnrs.fr\/\" target=\"_blank\">Godichon-Baggioni, A.<\/a>, Maugis-Rabusseau, C. and <a href=\"http:\/\/andrea-rau.com\" target=\"_blank\">Rau, A.<\/a> (2019) Clustering transformed compositional data using <em>K<\/em>-means, with applications in gene expression and bicycle sharing system data.\u00a0<em>Journal of Applied Statistics, 46, 47-65.<\/em><br \/>\n[<a href=\"http:\/\/arxiv.org\/abs\/1704.06150\">arXiv:1704.06150<\/a>] [<a href=\"https:\/\/hal.archives-ouvertes.fr\/hal-01511574v2\/document\" target=\"_blank\">Hal-01511574<\/a>]<\/li>\n<li>Sauvage, C., <strong><a href=\"http:\/\/andrea-rau.com\" target=\"_blank\">Rau, A.<\/a><\/strong><strong>,<\/strong> Aichholz, C., Chadoeuf, J., Sarah, G., Ruiz, M., Santoni, S., Causse, M., David, J., Gl\u00e9min, S. (2017)<br \/>\nDomestication rewired gene expression and nucleotide diversity patterns in tomato. <em>The Plant Journal,<\/em> 91(4):631-645.<\/li>\n<li><a href=\"http:\/\/perso.math.univ-toulouse.fr\/laurent\" target=\"_blank\">Laurent, B.\u00a0<\/a>,\u00a0<a href=\"http:\/\/math.univ-lyon1.fr\/~marteau\/index.html\" target=\"_blank\">Marteau, C.<\/a>\u00a0and Maugis-Rabusseau, C. (2017).<br \/>\nMultidimensional two-component Gaussian mixtures detection. <em>Annales de l&#8217;IHP (s\u00e9rie B)<\/em>, 54(2), 842-865.<br \/>\n[<a href=\"http:\/\/arxiv.org\/abs\/1509.09129\">arXiv:1509.09129<\/a>] [<a href=\"https:\/\/hal.archives-ouvertes.fr\/hal-01207072v1\">Hal-01207072<\/a>]<\/li>\n<li><a href=\"http:\/\/andrea-rau.com\" target=\"_blank\">Rau, A<\/a>. &amp; Maugis-Rabusseau, C. (2018) Transformation and model choice for RNA-seq co-expression analysis.<em>\u00a0Briefings in Bioinformatics<\/em>, 19(3), 65-76.<br \/>\n[<a href=\"http:\/\/dx.doi.org\/10.1101\/065607\" target=\"_blank\">bioRxiv, doi: http:\/\/dx.doi.org\/10.1101\/065607<\/a>]<\/li>\n<li><a href=\"http:\/\/perso.math.univ-toulouse.fr\/gadat\/\" target=\"_blank\">Gadat, S. <\/a>&amp; Kahn, J. &amp;\u00a0<a href=\"http:\/\/math.univ-lyon1.fr\/~marteau\/\">Marteau, C.<\/a> &amp; Maugis-Rabusseau, C.\u00a0Parameter recovery in two-component contamination mixtures: the L2 strategy\u00a0(2016) Submitted.[<a href=\"https:\/\/arxiv.org\/abs\/1604.00306\">arXiv:1604.00306<\/a>]<\/li>\n<li>G. Rigaill, S. Balzergue, V. Brunaud, E. Blondet, A. Rau, O. Rogier, J. Caius, C. Maugis-Rabusseau,\u00a0L. Soubigou-Taconnat, S. Aubourg, C. Lurin, M.-L. Martin-Magniette and E. Delannoy(2016) Synthetic datasets for the identification of key ingredients for RNA-seq differential analysis. <em>Briefings in bioinformatics<\/em>, 19(1), 65-76.<\/li>\n<li><a href=\"http:\/\/math.univ-lille1.fr\/~biernack\/\" target=\"_blank\">C. Biernacki<\/a> &amp; C. Maugis-Rabusseau. Chapitre 9 : &#8220;High-dimensional clustering&#8221;. Model choice and Model aggregation, sous la direction de F.BERTRAND, J-J. DROESBEKE, G. SAPORTA, C. THOMAS-AGNAN Edition Technip.\u00a0Septembre 2017.<\/li>\n<li><a href=\"https:\/\/www6.inra.fr\/mia-paris\/Equipes\/Membres\/Marie-Laure-Martin-Magniette\" target=\"_blank\">Martin-Magniette, M.-L.<\/a>, Maugis-Rabusseau, C. and <a href=\"http:\/\/www4.jouy.inra.fr\/gabi\/Presentation\/Annuaire-des-pages-personnelles\/RAU-Andrea\" target=\"_blank\">Rau, A<\/a>. Chapitre 10 : &#8220;Clustering of co-expressed genes&#8221;. Model choice and Model aggregation, sous la direction de F. BERTRAND, J-J. DROESBEKE, G. SAPORTA, C. THOMAS-AGNAN Edition Technip. Septembre 2017.<\/li>\n<li><a href=\"http:\/\/www4.jouy.inra.fr\/gabi\/Presentation\/Annuaire-des-pages-personnelles\/RAU-Andrea\" target=\"_blank\">Rau, A.<\/a>,\u00a0Maugis-Rabusseau, C. ,\u00a0<a href=\"https:\/\/www6.inra.fr\/mia-paris\/Equipes\/Membres\/Marie-Laure-Martin-Magniette\" target=\"_blank\">Martin-Magniette, M.-L.<\/a>\u00a0and <a href=\"http:\/\/www.math.u-psud.fr\/select\/people\/celeux\/Welcome.html\" target=\"_blank\">Celeux, G.<\/a>\u00a0(2015).<br \/>\nCo-expression analysis of high-throughput transcriptome sequencing\u00a0data with Poisson mixture models. <em>Bioinformatics<\/em>, 31 (9), 1420-1427.<br \/>\n<span style=\"font-size: 16px\">\u00a0<\/span><a style=\"font-size: 16px\" href=\"http:\/\/hal.inria.fr\/index.php?halsid=rju9i0qaa7n07nhlav76vmrh65&amp;view_this_doc=inria-00638082&amp;version=1\" target=\"_blank\">[Hal-INRIA, RR-7786]<\/a><span style=\"font-size: 16px\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 [<\/span><a style=\"font-size: 16px\" href=\"http:\/\/cran.r-project.org\/web\/packages\/HTSCluster\/index.html\" target=\"_blank\">R package HTSCluster<\/a><span style=\"font-size: 16px\">].<\/span><\/li>\n<li><a href=\"http:\/\/perso.math.univ-toulouse.fr\/laurent\" target=\"_blank\">Laurent, B.<\/a>,\u00a0<a href=\"http:\/\/math.univ-lyon1.fr\/~marteau\/index.html\" target=\"_blank\">Marteau, C.<\/a>\u00a0and Maugis-Rabusseau, C. (2016).\u00a0Non asymptotic detection of two component mixtures with unknown means.\u00a0<em>Bernoulli<\/em>, Volume 22, Number 1, 242-274.<br \/>\n<a href=\"http:\/\/arxiv.org\/pdf\/1304.6924v2.pdf\" target=\"_blank\">[arXiv:1304.6924]<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Mondet, F.,\u00a0Rau, A., Klopp, C., Rohmer, M. Severac, D., Le Conte, Y., and Alaux, C.(2018). Transcriptome profiling of the honeybee parasite Varroa destructor provides new biological insights into the mite adult life cycle. BMC Genomics, 19(1):328. Celeux, G., Maugis-Rabusseau, C. and Sedki, M. (2018). Variable selection in model-based clustering and discriminant analysis with regularization approach. [&hellip;]<\/p>\n","protected":false},"author":128,"featured_media":0,"parent":126,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-210","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/perso.math.univ-toulouse.fr\/maugis\/wp-json\/wp\/v2\/pages\/210","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/perso.math.univ-toulouse.fr\/maugis\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/perso.math.univ-toulouse.fr\/maugis\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/perso.math.univ-toulouse.fr\/maugis\/wp-json\/wp\/v2\/users\/128"}],"replies":[{"embeddable":true,"href":"https:\/\/perso.math.univ-toulouse.fr\/maugis\/wp-json\/wp\/v2\/comments?post=210"}],"version-history":[{"count":38,"href":"https:\/\/perso.math.univ-toulouse.fr\/maugis\/wp-json\/wp\/v2\/pages\/210\/revisions"}],"predecessor-version":[{"id":399,"href":"https:\/\/perso.math.univ-toulouse.fr\/maugis\/wp-json\/wp\/v2\/pages\/210\/revisions\/399"}],"up":[{"embeddable":true,"href":"https:\/\/perso.math.univ-toulouse.fr\/maugis\/wp-json\/wp\/v2\/pages\/126"}],"wp:attachment":[{"href":"https:\/\/perso.math.univ-toulouse.fr\/maugis\/wp-json\/wp\/v2\/media?parent=210"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}