Invited Speakers of past Editions

  • P. Alquier (ENSAE ParisTech & Paris Saclay)

  • C. Ané (U. Wisconsin, USA)

  • S. Arlot (École Normale Supérieure, Paris), Cross-validation for estimator selection

  • F. Austerlitz (MNHN , France)

  • Guy Baele (KU Leuven, Belgium), Incorporating individual travel histories in Bayesian phylogeographic inference of SARS-CoV-2

  • N. Beerenwinkel (ETH, Zurich, Switzerland)

  • K. Borgwardt  Beyond the Support Vector Machine: Kernels in Bioinformatics

  • Helen Byrne (Oxford University) : Approaches to understanding tumour-immune interactions

  • Mathieu Carrière(Sophia Antipolis, INRIA), An introduction to Topological Data Analysis and its application to genomic data

  • R Chikhi (CRIStAL, Lille)

  • Simona Cocco (Ecole des Neurosciences Paris Île de France, Paris)

  • V. Colot (Ecole Normale Supérieure, Paris), Epigenetic variation across generations 

  • J. Corander (U. of Oslo & U. Helsinki)

  • Juan Cortés (CNRS, Toulouse) : A data-driven approach for modeling highly-flexible proteins and regions

  • A. Dalalyan (ENSAE, CREST, France)

  • M. El-Karoui (INRA), Some biological questions in comparative genomics

  • G. Filion (Centre of Genomic Regulation, Barcelona), Promoters interpret the chromatin context in different ways

  • Georg Daniel FÖRSTER et al. Inference of the populations of protein structure ensembles from NMR chemical shift data

  • Julia Gog (University of Cambridge, Cambridge, UK)

  • Marina Gomtsyan et al. Variable selection in sparse GLARMA models

  • Boris Hejblum (Université de Bordeaux) : Distribution-free complex hypothesis testing for single-cell RNA-seq differential expression analysis

  • Ruth Heller (Tel Aviv University, Israel) Estimation and testing following aggregated association tests

  • T. Hothorn (Universität Zürich), From the Cox-Model to Conditional Transformation Models and Back

  • W. Huber (European Molecular Biology Laboratory, Heidelberg, Pharmacogenomics of targeted drug response in tumours

  • Iuliana Ionita-Laza (Columbia University) Knockoff-based statistics for the identification of putative causal loci in genetic studies

  • Geert-Jan Huizing et al. Optimal Transport improves cell-cell similarity inference in single-cell omics data

  • Laurent Jacob (CNRS, LBBE, Université Lyon 1, Lyon)

  • D.T. Jones (UCL, UK),

  • Louis Lambrechts (Institut Pasteur, Paris)

  • Fabien Laporte et al. MM4LMM: a R package to infer variance component mixed models

  • N. Lawrence (U. Sheffield), Between Systems and Data-driven Modeling for Computational Biology: Target Identification with Gaussian Processes

  • Martial Marbouty (Institut Pasteur, Paris)

  • F. Markowetz (CR UK - CRI, Cambridge, UK)

  • François Massol (CNRS, Lille) : Analyzing determinants of gut microbiota using interaction network methods

  • Eleni Matechou (Senior lecturer, University of Kent) : New statistical methods for eDNA data

  • C. Matias (CNRS, Univ. Evry), Statistical Alignment

  • Gildas Mazo et al. Statistical multivariate modelling of omics data with copulas

  • G. Mc Vean (Univ. of Oxford), A fine-scale map of the chimpanzee from population scale sequencing

  • Peter Mueller (UT Austin, USA) The future of Bayesian clinical trial design

  • Axel Munk (Institut für Mathematische Stochastik, Goettingen)

  • H.-G. Müller (U. California, Davis), Functional Regression Models and Applications 

  • W. Noble (University of Washington), The one-dimensional and three-dimensional architecture of the genome

  • Guido Nolte (Fraunhofer Institute for Intelligent Analysis and Information Systems) Estimation of causal direction from time series in the presence of mixed and colored noise

  • Mitsuhiro Odaka et al. Exploring Differential Equations for Modeling SARS-CoV-2 Dynamics with Sensitivity and Stability Analysis

  • Hervé Perdry (Université Paris-Saclay, INSERM), Fast methods for mixed logistic regression in genome-wide association studies

  • Florian Privé ( Aarhus University, Denmark), Predicting traits and diseases from genetic data

  • Elizabeth Purdom (UC Berkeley, USA), Estimation of lineage trajectories from single cell mRNA data

  • Lluis Quintana Murci (Institut Pasteur, France), Evolutionary genetic dissection of the genus Homo and its immune response

  • Manon Ragonnet-Cronin (Imperial College London) , Insights into SARS-CoV-2 spread from viral genetic data

  • P. Reynaud (Nice University), Hawkes process as models for some genomic data

  • S. Richardson (MRC Biostatistics Unit, Cambridge, UK)

  • Hélène Ruffieux et al. EPISPOT: an epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies

  • Yvan Saeys (Ghent University),Towards robust feature selection for high-dimensional, small sample settings

  • Yvan Saeys (Ghent University, Belgium), Modeling cellular dynamics and communication from single-cell data: a machine learning perspective

  • Thomas Schiex (INRAE, Toulouse) : Automated reasoning and learning for Computational Protein Design

  • Catherine Schramm et al. Penetrance estimation of Alzheimer disease in SORL1 loss-of-function variant carriers using a family-based strategy adjusted on APOE genotypes

  • B. Schwikowski (Institut Pasteur)

  • Hervé Seitz (IGH, Montpellier)

  • Pierre-Emmanuel Sugier et al. Advanced Bayesian meta-analysis methods for investigating pleiotropy effect

  • A. van der Vaart (Leiden University, Leiden, The Netherlands)

  • A. Veber (Ecole Polytechnique, Palaiseau), Evolution in a spatial continuum

  • Marie Verbanck (Université de Paris) Tissue-specific genetic features inform prediction of drug side effects in clinical trials

  • N. Verzelen (INRA, Montpellier), Some limits to high-dimensional estimation

  • D. Wilkinson (New Castle University),  Bayesian inference for biochemical network dynamics

  • Marti-Renom (CRG-CNAG, Barcelona),

  • Aleksandra Walczak (Ecole Normale Supérieure, Paris)

  • Ariane Weber (TIDE, Max Planck Institute, Deutschland), Quantification of SARS-CoV-2 transmission through time and betweenlineages using phylodynamics

  • Maite Wilke Berenguer(Assistant professor Ruhr-Universität Bochum) : Lambda-coalescents arising from dormancy

  • Marloes Maathuis (ETH, Zurich)

  • Katharina Proksch (Ruhr University, Bochum)

  • Wencan ZHU et al. A variable selection approach for highly correlated predictors in high-dimensional genomic data

  • Anna Zhukova et al. Fast and Accurate Resolution of the Birth-Death Exposed-Infectious (BDEI) Model

 

Past Themes (and session organizers)

  • Cancer applications (2009, E. Barillot)

  • Large dimension data (2009, F. Picard)

  • Phylogeny (2009, 2014, A. Bar-Hen, N. Lartillot)

  • Network Analysis (2010, C. Ambroise, 2013, S. Mukherjee)

  • Feature Selection (2010, B. Ghattas)

  • multiple testing (2011, J. Goeman)

  • Statistical genetics (2011,M.L. Taupin)

  • High-throughput sequencing (2011, 2012)

  • Data Integration (2012, J.-P. Vert)

  • Ecology and Genomics (2012, H. Morlon)

  • Metagenomics (2013, J.-J. Daudin)

  • Design & sample size (2013, M. Langaas, R. de Menezes)

  • Metabolism (2014, D. Kahn)

  • Statistical Genomics (2014, B. Servin)

  • Single Cell genomics (2015, J. Marioni, 2018, F. Picard)

  • Systems Genetics (2015, J. Gagneur)

  • Epigenomics (2015, F. Picard)

  • Change-point detection (2016, A. Célisse)

  • Epidemiology (2016, T.V. Chi)

  • GWAS for prokaryotes (2016, L. Jacob)

  • Big data in biology (2017)

  • medicine and health, and precision medicine, (2017)

  • Bayesian biostatistics and machine learning in bioinformatics, (2017)

  • Computational epidemiology and evolutionary models, (2017)

  • Systems biology and networks (2017)

  • Evolutionary models and Bayesian inference (2018, P. Pudlo)

  • Non parametric Bayes and Health (2018, A. Cleynen)

  • Analysis of biological images (2019, Jean-Christophe Olivo-Marin),

  • Causal inference (2019 Vivian Viallon),

  • Genome conformation (2019, Guillaume Filion)

  • Evolution of inter-species interactions (2020, organized by Bastien Boussau and Damien de Vienne)

  • Machine learning algorithms for computational biology (2020, organized by Chloé-Agathe Azencott) 

  • Evolution and epidemiology (2020, organized by Amandine Véber)

  • Environmental DNA (2021, organized by Julyan Arbel and Alexandros Stamatakis)

  • Genomics in Biomedical Research (2021, organized by Franck Picard)

  • SpatioTemporal Evolution & population Genetics (2021, organized by Amandine Veber)

  • Artificial Intelligence methods for protein modeling and design (2021, organized by Pierre Neuvial)

  • Next Generation Association Studies (2022)

  • Single-Cell and Intercellular Communication (2022)

  • Sarscov2, Epidemiology and Phylodynamics (2022)

  • Topological Data Analysis and other methods (2022)