Persyvact2

Persyvact2 is composed of about twenty researchers from GIPSAlab, LJK, and TIMC-IMAG. Coming from various fields related to data science (statistics, machine learning, image and signal processing), the members of Persyvact2 will analyze biomedical data generated by neuroscience, genomics, and clinical trial research. The key structures of the biomedical data that Persyvact2 will exploit are graph structures, repeated experiments, and their intrinsic low-dimensional representations.

The goal of Persyvact2 is to conduct collaborative research and bring together researchers from various scientific fields who are interested in data science. Persyvact2 plans to organize scientific events and an international workshop during its term. Persyvact2 aims to enhance the international visibility of data science in Grenoble.

Keywords: Computational and theoretical statistics; multimodal and heterogeneous data; image and signal processing; spatial analysis; graphical models; mixed models; learning; structure extraction; (un)supervised classification; detection; point processes; large-scale optimization; regularization (convex or non-convex, differentiable or non-differentiable); Bayesian analysis; multiscale analysis; Markov models; latent variable models; dimensionality reduction; scattering; model selection; robustness; statistical neuroscience; genetics; medical imaging.

Coordinators

Pierre-Olivier Amblard (Gipsa-lab)
Michael Blum (TIMC-IMAG)
Adeline Leclercq-Samson (LJK)

Members

Sophie Achard (Gipsa-lab)
Pierre-Olivier Amblard (Gipsa-lab)
Hacheme Ayasso (Gipsa-lab)
Caroline Bazzoli (LJK)
Michael Blum (TIMC-IMAG)
Jean-Marc Brossier (Gipsa-lab)
Florent Chatelain (Gipsa-lab)
Laurent Condat (Gipsa-lab)
Michel Desvignes (Gipsa-lab)
Rémy Drouilhet (LJK)
Florence Forbes (LJK)
Olivier François (TIMC-IMAG)
Stéphane Girard (LJK)
Sophie Lambert (TIMC-IMAG)
Adeline Leclercq-Samson (LJK)
Frédérique Letué (LJK)
Julien Mairal (LJK)
Marie-José Martinez (LJK)
Olivier Michel (Gipsa-lab)
Nicolas Thierry-Mieg (TIMC-IMAG)
Laurent Zwald (LJK)

Seminars and meetings

• Cancer Heterogeneity Data Challenge. December 10–14, 2018
• Summer School on Signal Processing on Graphs. September 10–14, 2018
• Graduate Training Program in Data Science for Geosciences. January 15–19, 2018
• Epigenetic & High-Dimensional Data Challenge. June 7–9, 2017
• Workshop on "Modeling in Biology and Biomedical Data Statistics." November 2, 2015

Publications

Choiruddin A, J.-F. Coeurjolly, F. Letué (2018) Convex and non-convex regularization methods for estimating the intensity of spatial point processes. Electronic Journal of Statistics

Prive F, H Aschard, A Ziyatdinov, MGB Blum (2018) Efficient management and analysis of large-scale genome-wide data using two R packages: bigstatsr and bigsnpr. Bioinformatics 34:2781-2787

Capblancq T, K Luu, MGB Blum, E Bazin (2018) How to use ordination methods to identify local adaptation: a comparison of genome scans based on PCA and RDA. Molecular Ecology Resources

Dias-Alves T, J Mairal, MGB Blum (2018) Loter: A software package for inferring local ancestry across a wide range of species. Molecular Biology and Evolution, 126

Bacher R, Meillier C, Chatelain F, Michel O (2017) Robust control of varying weak hyperspectral target detection using sparse non-negative representation. IEEE Transactions on Signal Processing 65:3538–3550

Cubry P, Vigouroux Y, François O (2017) The empirical distribution of singletons in geographic samples of DNA sequences. Frontiers in Genetics 8

Gabriel Zebadua A, P-O Amblard, E Moisan, OJJ Michel (2017)Compressed and Quantized Correlation Estimators. IEEE Transactions on Signal Processing 65:56–68

Luu K, Bazin E, Blum MGB (2017)pcadapt: an R package for performing genome-wide scans for selection based on principal component analysis.Molecular Ecology Resources 1:67–77

Le Bihan N, F Chatelain, J Manton (2016) Isotropic Multiple Scattering Processes on Hyperspheres. IEEE Transactions on Information Theory 62:5740–5752

Grenier E, Helbert C, Louvet V, Samson A, Vigneaux P (2016)Population parametrization of costly black-box models using iterations between the SAEM algorithm and kriging. Computational and Applied Mathematics.

Delattre M, Genon-Catalot V, Samson A (2016)Mixtures of stochastic differential equations with random effects: application to data clustering. Journal of Statistical Planning and Inference.

F. Harlé, F. Chatelain, C. Gouy-Pailler, S. Achard. " Bayesian Model for Multiple Change-Point Detection in Multivariate Time Series" (2016). *IEEE Transactions on Signal Processing* 

Ollier E, Samson A, Delavenne X, Viallon V (2016)A SAEM Algorithm for Fused Lasso Penalized Nonlinear Mixed-Effect Models: Application to Group Comparison in Pharmacokinetics. Computational Statistics and Data Analysis. 96:207–221.

Martins H, Caye K, Luu K, Blum MGB, François O (2016)Identifying outlier loci in admixture and continuous populations using ancestral population differentiation statistics. Molecular Ecology25:5029–5042

Duforet-Frebourg N, Luu K, Bazin E, Blum MGB (2016). Detecting Genomic Signatures of Natural Selection with Principal Component Analysis: Application to the 1000 Genomes Data.Molecular Biology and Evolution. 33:1082-1093 

Termenon M, C Delon-Martin, A Jaillard, S Achard (2016). Reliability of graph analysis of resting-state fMRI using a test-retest dataset from the Human Connectome Project. Neuroimage 142: 172–187.

Termenon M, S Achard, A Jaillard, C Delon-Martin (2016). The “hub disruption index,” a reliable index sensitive to the reorganization of brain networks: a study of the contralesional hemisphere in stroke. Frontiers in Computational Neuroscience 10.