David Causeur
Présentation
Publications
Publications
Inferring cellular heterogeneity with mixture models for DNA methylation rates (SMPGD 2026)SMPGD 2026, Jan 2026, Grenoble, France |
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Inferring cellular heterogeneity with mixture models for DNA methylation ratesJdS, Jun 2025, Marseille, France |
Multi-omic statistical inference of cellular heterogeneity - IGDR SCAN 26/03/2025IGDR SCAN, Mar 2025, Rennes (CHU), France |
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Multi-omic statistical inference of cellular heterogeneity - JOBIM 2024JOBIM 2024, Jun 2024, Toulouse, France |
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Multi-omic statistical inference of cellular heterogeneity - JdS 2024JdS 2024, May 2024, Bordeaux, France |
Statistical modeling of in vitro pepsin specificityVirtual International Conference on Food Digestion, Cost Infogest, May 2021, Virtual International Conference on Food Digestion (#VICFD2021) on 6-7th May 2021., France |
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Statistical modelling of in vitro pepsinolysis using peptidomic dataJournées Scientifiques de l'ED EGAAL 2021, L’école doctorale « Écologie, Géosciences, Agronomie, ALimentation, Jun 2021, Rennes, France |
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Prediction of fatty acids in the rainbow trout Oncorhynchus mykiss: a Raman scattering spectroscopy approach22. International Conference on Transparent Optical Networks (ICTON), Jul 2020, Bari, Italy. pp.1-4, ⟨10.1109/ICTON51198.2020.9203514⟩ |
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Identification of the physicochemical characteristics of peptides that influence their hydrolysis by pepsinWorkshop Infogest statistical treatment of peptidomic data, Institut National de Recherche Agronomique (INRA). UMR UMR INRA / AgroCampus Rennes : Science et Technologie du Lait et de l'?uf (1253)., Dec 2019, Lyon, France |
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Décorrélation adaptative pour la prédiction en grande dimension51es Journées de Statistique 2019, Société Française de Statistique, Jun 2019, Nancy, France |
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PROPENSITY WEIGHTING FOR SURVEY NONRESPONSE THROUGH MACHINE LEARNING13es Journées de méthodologie statistique de l'Insee (JMS), Jun 2018, Paris, France |
Identification des fonctions biologiques, spécifiques d’un tissu ou partagées entre tissus, associées aux différences d’efficacité alimentaire chez le porc en croissance49. Journées de la Recherche Porcine, Jan 2017, Paris, France. pp.13-18 |
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Variable selection for correlated data in high dimension using decorrelation methodsStatlearn: Challenging problems in statistical learning, Apr 2016, Vannes, France |
Data integrationMeeting INRA-ISU, Mar 2015, Ames, United States. 11 diapositives |
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FADA: an R package for variable selection in supervised classification of strongly dependent datauseR!2014, UCLA Statistics Department; Foundation for Open Access Statistics; Los Angels R user group, Jun 2014, Los Angeles, United States |
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Dealing with long-time range dependence in large-scale multiple testing of Event-Related Potentials data46e Journées de Statistique, Société Française de Statistique, Jun 2014, Rennes, France |
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ERP: an R package for Event-Related Potentials data analysisuseR!2014, UCLA Statistics Department; Foundation for Open Access Statistics; Los Angels R user group, Jun 2014, Los Angeles, United States |
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Sparse factor model for gene co-expression networksBioNetVisA Workshop, Sep 2014, Strasbourg, France |
Generalized linear factor modeling for dependence between SNPs in GWASStatistical fort Genomic Data (SMPGD'13), Jan 2013, Amsterdam, Netherlands |
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Stabilité de la sélection de variables pour la classification de données en grande dimension45 èmes Journées de Statistique, May 2013, Toulouse, France |
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Inferring gene networks using a sparse factor model approachStatistical learning and data science, May 2012, Florence, Italy. 12 p |
Inférence de réseaux de co-expression génique10ème Journée Biogenouest, Nov 2012, Rennes (FR), France. non paginé |
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Inferring gene networks using a sparse factor model approach, Statistical Learning and Data ScienceLearning and Data Science, May 2012, Florence (IT), Italy |
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Transcriptome profiling reveals interaction between two QTL for fatness in chicken15th European workshop on QTL mapping and marker assisted selection (QTLMAS), May 2011, Rennes (FR), France. 1 p |
Genetic analysis of a complex trait using transcriptomic data: contribution of gene regulatory network modelingXX. Conference of the plant & animal genome (PAG), Jan 2012, San Diego, United States. 1 p |
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Sparse factor models for gene co-expression networks.Séminaire de Biostatistiques, Dec 2012, Toulouse (FR), France. non paginé |
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Selection stability for supervised classification of heterogeneous data.Selection stability for supervised classification of heterogeneous data., Oct 2011, Rennes (FR), France. non paginé |
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Large-scale significance testing of high thoroughput Data with FAMT14. Conference of the Applied Stochastic Models and Data Analysis International Society, Jun 2011, Rome, Italy |
Effect of the gene diacylglycerol-O-transferase 1 (DGAT1) polymorphism on the global expression pattern of genes in the mammary gland tissue of dairy cows62. Annual Meeting of the European Federation of Animal Science (EAAP), Aug 2011, Stavanger, Norway |
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Feature selection stability in high-dimensional heterogeneous data.Cladag 2011, Sep 2011, Pavia (IT), Italy. non paginé |
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Integrating QTL controlling fatness, lipid metabolites and gene expressions to genetically dissect the adiposity complex trait in a meat chicken cross62. Annual Meeting of the European Association for Animal Production (EAAP), Aug 2011, Stavanger, Norway |
Integrating biological knowledge in gene expression data analysisISI 2011, Aug 2011, Dublin (IE), Ireland. non paginé |
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Inférence sur réseaux géniques par Analyse en Facteurs42èmes Journées de Statistique, 2010, Marseille, France, France |
A factor model to analyze heterogeneity in gene expression in a context of QTL mapping8th workshop " Statistical Methods for Post-Genomic Data ", Jan 2010, Marseille, France |
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Estimation conditionnelle de la proportion d'hypotheses nulles en grande dimension41èmes Journées de Statistiques, Société Française de Statistiques, May 2009, Bordeaux, France |
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Factor Analysis for Multiple Testing (FAMT) : an R package for simultaneous tests under dependence in high-dimensional dataUseR!2009. Agrocampus, Jul 2009, Rennes, France |
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Estimation conditionnelle de la proportion d'hypothèses nulles en grande dimension41èmes Journées de Statistique, SFdS, Bordeaux, 2009, Bordeaux, France, France |
Conditional Fdr estimation based on a factor analytic approach of multiple testingWorkshop on Simulation, Jun 2009, St Petersburg, Russia |
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Factor Analysis for Multiple Testing: a general approach for differential analysis of genome-scale dependent dataWorkshop on Statistical advances in Genome-scale Data Analysis, May 2009, Ascona, Switzerland |
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Factor Analysis for Multiple Testing: an R-package to analyze a genome-scale datasetWorkshop « Statistical advances in Genome-scale Data Analysis », May 2009, Ascona, Switzerland |
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Estimation of the proportion of null p-values among dependent testsPetersburg Workshop on Simulation, Jun 2009, St Petersburg, Russia |
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Improving supervised classification for high dimensional data by adding external information. Application to microarray dataAnnual conference of the Société française de Statistique (SFdS) and the Statistical Society of Canada (SSC), May 2008, Ottawa, Canada |
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Approche conditionnelle des tests multiples pour données biologiques à haut-débit7ème Journée Jeunes Chercheurs (Société Française de Biométrie). INSERM, Dec 2008, Villejuif, France |
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Multiple tests for high-throughput data assuming a factor modeling of dependence40th Journées de Statistiques (Société Française de Statistiques) / joint with Société Statistique, May 2008, Ottawa, Canada |
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Impact of Dependence on the Stability of Model Selection in Supervised Classification for High-Throughput DataInternational Indian Statistical Association (IISA) Conference on Frontiers of Probability and Statistical Science, May 2008, Storrs, United States |
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Accounting for a factor structure in high-dimensional data to improve multiple testing procedures6th workshop on Statistical Methods for Post-Genomic Data. Agrocampus, Feb 2008, Rennes, France |
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Reducing the non-discovery rate by use of auxiliary variables in microarray experiments5. Workshop Statistical Methods for Post-Genomic Data (SMPGD), Jan 2007, Paris, France. 2 p |
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Improving type II error rates of multiple tests by use of auxiliary variables. Application to microarray dataXIIth International conference on Applied Stochastic Models andData Analysis (ASMDA2007), May 2007, Chania, Greece |
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Variations in mammary extraction of nutrients under the effect of a 36-h milk accumulation into the udder in dairy cows2. International Symposium on Energy and protein metabolism and nutrition ISEP, Sep 2007, Vichy, France |
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Reducing the Non-Discovery Rate by use of auxiliary variables in microarray experiments5th Workshop: Statistical methods for post-genomic data, Jan 2007, Paris, France |
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Maximizing piglet survival57th Annual Meeting of the European Association for Animal Production, Sep 2006, Antalya, Turkey |
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Facteurs de variation de la détection des chaleurs chez la vache laitière conduite en vêlages groupésXIIIè Rencontres recherche ruminants, Dec 2006, Paris, France |
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Facteurs de variation de la détection des chaleurs chez la vache laitière conduite en vêlages groupés13. Rencontres Recherches Ruminants, Dec 2006, Paris, France |
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Maximising piglet survival57. Annual Meeting of the European Association for Animal Production, Sep 2006, Antalya, Turkey |
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Prédiction de la composition chimique des truies reproductrices à partir du poids vif et de l'épaisseur de lard dorsal : Application à la définition des besoins énergétiques29. Journées de la recherche porcine en France, Feb 1997, Paris, France |
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Prediction sur matrices de distancesJournees de Statistique, May 1993, Vannes, France |
Evaluation of linear modeling assumptions in a simulation context for deconvolution of multi-omic dataJournée de Biologie In Silico de Rennes, Nov 2025, Rennes, France. |
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Simulation of data-driven multi-omic benchmark data for cellular deconvolution methods evaluationIGDR PhD symposium, Nov 2024, Rennes (Campus de Beaulieu), France. 2024 |
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Multi-omic statistical inference of cellular heterogeneity - COBICA 2024cobica2024 : Computational Biology of Cancer 2024, Mar 2024, Grenoble, France |
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Integrative responses of pig adipose tissues to high-fat high-fiber diet: towards key regulators of energy flexibilityASAS/ADSA midwest meeting, Mar 2015, Des Moines, United States. Journal of Animal Science, 93 (Suppl. 2), 2015, Abstract book of the ASAS/ADSA midwest meeting |
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The R package FANet: sparse factor analysis model for high dimensional gene co-expression networksThe International R Users Conference, Jun 2014, Los Angeles, United States. 2014, UserR contributed abstracts |
How food protein structure can modulate the protein digestion behaviour: Evaluation by nutritional peptidomicsFood Structure and Functionality Forum Symposium from Molecules to Functionality, Mar 2014, Amsterdam, Netherlands. 2014 |
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Quantitative Mass Spectrometry for nutritional peptidomics Evaluating the impact of food processing by multivariate statistical approachesEUPA 2013, Oct 2013, Saint-Malo, France. 2013 |
Factor modelling of multiple time series to detect temporal variations in common dynamics4. Channel Network Conference - IBS (International Biometry Society), Jul 2013, Saint Andrews, United Kingdom. 2013 |
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A factor model to analyse heterogeneity in gene expression in a context of QTL characterizationXXXII International Conference on Animal Genetics (ISAG), Jul 2010, Edinburgh, United Kingdom. 2010, Proceedings of the 32nd International Conference on Animal Genetics |
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Transcriptome profiling reveals interaction between two QTL for fatness in chickenXXXII International Conference on Animal Genetics (ISAG), Jul 2010, Edinburgh, United Kingdom. 2010, Proceedings of the 32nd International Conference on Animal Genetics |
Improving Type-II error rates of multiple testing procedures by use of auxiliary variables. Application to microrray dataRecent advances in Stochastic Modelling and data Analysis, World Scientific, pp.645-xx, 2007 |
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How to organise a scientific competition to benchmark methods and algorithms in computational biology?2026 |
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Signal identification in ERP data by decorrelated Higher Criticism Thresholding2016 |
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Large-scale significance testing of the full Moon effect on deliveries2009 |