SMPGD 2017 features 52 presentations with 25 talks and 27 poster presentations.
The detailed schedule is shown below. Please download the abstract book (54 pages, PDF) that contains the submitted abstracts and the programme.
| Day 1 |
Theme 1: Big Data in Biology, Medicine and Health, and Precision Medicine | ||
| 9:00 | Opening | Korbinian Strimmer (ICL), Marc Chadeau-Hyam (ICL) | |
| 9:10 | Keynote 1: | Neil Lawrence (Amazon Cambridge, Sheffield) | Personalized health: challenges in data science |
| 10:00 | Invited 1: | Alex Lewin (Brunel) | Bayesian inference on high-dimensional seemingly unrelated regressions, applied to metabolomics data |
| 10:30 | Contributed: | Kieran Campbell (Oxford) | Stratification of patient trajectories using covariate latent variable models |
| 10:50 | Coffee Break | ||
| 11:10 | Invited 2: | Mark van de Wiel (VU and VUMC Amsterdam) | Empirical Bayes learning from co-data in high-dimensional prediction settings |
| 11:40 | Contributed: | Verena Zuber (EBI Hinxton) | Two-dimensional fine-mapping of global and molecular traits to identify gene-disease linkages |
| 12:00 | Contributed: | Christophe Ambroise (Évry) | Fast computation of genome-metagenome interaction effect |
| 12:20 | Lunch Break | ||
| Theme 2: Bayesian Biostatistics and Machine Learning in Bioinformatics | |||
| 13:40 | Keynote 2: | Pierre Alquier (ENSAE Paris Saclay) | On the properties of variational approximations of posteriors and pseudo-posteriors |
| 14:30 | Invited 3: | Maria De Orio (UCL) | Bayesian inference for multiple Gaussian graphical models with application to metabolic association networks |
| 15:00 | Contributed: | Harry Gray (MRC BSU Cambridge) | Target-averaged linear shrinkage: high-dimensional covariance matrix estimation in functional genomics |
| 15:20 | Coffee Break | ||
| 15:40 | Invited 4: | Paul Kirk (MRC BSU Cambridge) | MDI: Multiple dataset integration using Bayesian correlated clustering |
| 16:10 | Contributed: | Dennis te Beest (VUMC Amsterdam) | Using co-data to improve the predictive accuracy of a random forest |
| 16:30 | Invited 5: | Silvia Liverani (Brunel) | Modelling collinear and spatially correlated data |
| 17:00 | Break – walk to poster presentations | ||
| 17:10 | Poster Presentations – All Topics (with refreshments) | ||
| 1 | Miika Ahdesmäki (AstraZeneca Cambridge) | Estimation of copy number variation calling uncertainty in NGS data from low pass and low tumour purity samples | |
| 2 | Lisa Amrhein (Helmholtz Munich) | Stochastic profiling for RNA Seq data | |
| 4 | Alessandra Cabassi (MRC BSU Cambridge) | Variational inference for semi-supervised clustering of ’omics data | |
| 3 | Julien Chiqet (INRA, Évry) | AriCode an R package to efficiently compute rand-index and other clustering comparison information measures |
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| 5 | Andrée Delahaye-Duriez (ICL, Paris Diderot, Sorbonne) | Rare and common epilepsies converge on a shared gene regulatory network providing opportunities for novel antiepileptic drug discovery | |
| 6 | Mathieu Emily (Rennes) | Gene-based gene-gene interaction with R | |
| 7 | Daniela Fecht (ICL) | Mining big data for environmental epidemiological analyses | |
| 8 | Anna Freni Sterrantino (ICL) | The multi pollutant profiles and cardiovascular mortality in London and Oxford (UK) | |
| 9 | Daniel Greene (MRC BSU Cambridge) | BeviMed: Bayesian evaluation of variant involvement in Mendelian disease | |
| 10 | Florent Guinot (Évry) | Are single nucleotides the right scale for genome-wide association studies | |
| 11 | Matthew Hall (Oxford) | Phyloscanner: evolutionary and phylodynamic analysis of NGS viral genome data | |
| 12 | Nazatulshima Hassan (Liverpool) | Novel tSNR as variable selection method for classification: an application to SNP data | |
| 13 | Boris Hejblum (Bordeaux) | Sequential Dirichlet process mixtures of multivariate skew t-distributions for model-based clustering of flow cytometry data | |
| 14 | Einar Holsbø (Tromsø, Paris Descartes) | Predicting breast cancer metastasis from blood gene expression using time-to-diagnosis data to derive signature estimates | |
| 15 | Alyssa Imbert (INRA Toulouse) | Multiple hot-deck imputation for network inference from RNA sequencing data | |
| 16 | Antonella Iuliano (Naples) | Network-based dimension reduction methods for the integrative analysis of multi-omics data in cancer | |
| 17 | Holger Kirsten (Leipzig) | Causal inferences in cross-sectional data – opportunities and drawbacks in the joint analysis of genomic, transcriptomic and metabolomic data | |
| 18 | Bernd Klaus (EMBL Heidelberg) | Data-driven hypothesis weighting increases detection power in genome-scale multiple testing | |
| 19 | Norbert Krautenbacher (Helmholtz Munich) | Prediction of childhood asthma risk by high-dimensional genetic and environmental data | |
| 20 | Magnus Munch (Leiden, VUMC Amsterdam) | Adaptive group-regularized logistic elastic net regression | |
| 21 | Miguel Pereira (ICL) | Integrating biological information through differential shrinkage in a Bayesian joint model: improving the analysis of genetic association studies | |
| 22 | Morgane Pierre-Jean (Évry) | A latent model to infer tumoral heterogeneity from DNA copy number profiles | |
| 23 | Clauda Rincon (Curie Paris) | Evaluation of different approaches to stratify somatic mutation profiles | |
| 24 | Oliver Robinson (ICL) | Metabolic effects of environmental pollutants in pregnant women – an exposome approach | |
| 25 | Tammo Rukat (Oxford) | The OrMachine, a model for dimensionality reduction of binary data with interpretable latent representations | |
| 26 | Benjamin Sadacca (Curie Paris) | Transcriptional analysis of two large-scale cancer cell line panels identifies novel insights for pharmacogenomics studies | |
| 27 | Virginie Stanislas (Évry) | Detecting interactions in GWAS with the gene-gene eigen epistasis approach | |
| 18:40 | End of poster session | ||
| 19:00 | Conference dinner (various restaurants nearby) | ||
| Day 2 | Theme 3: Computational Epidemiology and Evolutionary Models | ||
| 9:10 | Keynote 3: | Jukka Corander (Oslo, Helsinki) | Likelihood-free inference and predictions for computational epidemiology |
| 10:00 | Invited 6: | Phillippe Lemey (Leuven) | Connecting sequence and trait evolution in a Bayesian phylogenetic framework |
| 10:30 | Contributed: | Erik Volz (ICL) | Phylodynamic inference across epidemic scales |
| 10:50 | Coffee Break | ||
| 11:10 | Invited 7: | Tim Ebbels (ICL) | Power and sample size determination in metabolomics |
| 11:40 | Contributed: | Vinny Davies (Glasgow) | Sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution |
| 12:00 | Contributed: | Florian Hébert (Rennes) | Block testing approach in genome-wide association studies using a multilevel modeling of the dependence structure |
| 12:20 | Lunch Break | ||
| Theme 4: Systems Biology and Networks | |||
| 13:40 | Keynote 4: | Benno Schwikowski (Pasteur Paris) | LEAN discovery of hot spots in networks |
| 14:30 | Invited 8: | Sarah Filippi (Oxford, ICL) | Bayesian nonparametric approaches to quantifying dependence between random variables |
| 15:00 | Contributed: | Séverine Affeldt (Curie Paris, Sorbonne, Descartes) | Learning causal networks with latent variables from multivariate information in genomic data |
| 15:20 | Coffee Break | ||
| 15:40 | Contributed: | Wessel van Wieringen (VU and VUMC Amsterdam) | A tale of two networks |
| 16:00 | Contributed: | Gwenael Leday (MRC BSU Cambridge) | Gene network reconstruction using global-local shrinkage priors |
| 16:20 | Contributed: | Geneviève Robin (École Polytechnique Paris) | Graphical model inference with unobserved variables via latent tree aggregation |
| 16:40 | Invited 9: | Lorenz Wernisch (MRC BSU Cambridge) | Gene regulatory networks from single cell data |
| 17:10 | End of meeting | ||
| Further (co)authors and committee members present at workshop: | |||
| Marco Banterle (Brunel) | |||
| Magalie Berland (INRA, Jouy-en-Josas) | |||
| Etienne Birmelé (Paris Descartes) | |||
| Marta Blangiardo (ICL) | |||
| Isabel Brito (Curie Paris) | |||
| David Causeur (Rennes) | |||
| Marina Evangelou (ICL) | |||
| Magalie Houée-Bigot (Rennes) | |||
| Sylvie Huet (INRA, Jouy-en-Josas) | |||
| Cosetta Minelli (ICL) | |||
| Franck Picard (Lyon) | |||
| Stéphane Robin (INRA, AgroParisTech, Paris) | |||
| Michael Stumpf (ICL) | |||
| Ernest Turro (CRUK Cambridge) | |||
| Nathalie Villa-Vialaneix (INRA Toulouse) | |||
| Christopher Yau (Birmingham, Oxford) | |||
SMPGD 2017: Statistical Methods for Postgenomic Data 