| A quantitative multivariate model of human dendritic cell-T helper cell communication M Grandclaudon, M Perrot-Dockes, C Trichot, L Karpf, O Abouzid, ... Cell 179 (2), 432-447. e21, 2019 | 26 | 2019 |
| A multivariate Th17 metagene for prognostic stratification in T cell non-inflamed triple negative breast cancer L Faucheux, M Grandclaudon, M Perrot-Dockès, P Sirven, F Berger, ... Oncoimmunology, 2019 | 25 | 2019 |
| Variable selection in multivariate linear models with high-dimensional covariance matrix estimation M Perrot-Dockès, C Lévy-Leduc, L Sansonnet, J Chiquet Journal of Multivariate Analysis 166, 78-97, 2018 | 16 | 2018 |
| Estimation of large block structured covariance matrices: Application to ‘multi-omic’approaches to study seed quality M Perrot-Dockes, C Lévy-Leduc, L Rajjou Journal of the Royal Statistical Society Series C: Applied Statistics 71 (1 …, 2022 | 7 | 2022 |
| A variable selection approach in the multivariate linear model: an application to LC-MS metabolomics data M Perrot-Dockes, C Lévy-Leduc, J Chiquet, L Sansonnet, M Brégère, ... Statistical applications in genetics and molecular biology 17 (5), 20170077, 2018 | 7 | 2018 |
| A multivariate variable selection approach for analyzing LC-MS metabolomics data M Perrot-Dockès, C Lévy-Leduc, J Chiquet, L Sansonnet, M Brégere, ... arXiv preprint arXiv:1704.00076, 2017 | 6 | 2017 |
| Post hoc false discovery proportion inference under a Hidden Markov Model M Perrot-Dockès, G Blanchard, P Neuvial, E Roquain | 5 | 2021 |
| Easily Computed Marginal Likelihoods from Posterior Simulation Using the THAMES Estimator M Metodiev, M Perrot-Dockès, S Ouadah, NJ Irons, AE Raftery arXiv preprint arXiv:2305.08952, 2023 | 1 | 2023 |
| Variable Selection in the General Linear Model: Application to Multiomic Approaches for the Study of Seed Quality C LÉVY-LEDUC, M PERROT-DOCKÈS, G CUEFF, L RAJJOU Biological Data Integration: Computer and Statistical Approaches, 87-115, 2024 | | 2024 |
| Selective inference for false discovery proportion in a hidden Markov model M Perrot-Dockès, G Blanchard, P Neuvial, E Roquain TEST 32 (4), 1365-1391, 2023 | | 2023 |
| Sélection de variables dans le modèle linéaire général: application à des approches multiomiques pour étudier la qualité des graines C LÉVY-LEDUC, M PERROT-DOCKÈS, G CUEFF, L RAJJOU Intégration de données biologiques: Approches informatiques et statistiques, 101, 2022 | | 2022 |
| Sélection de variables dans le modèle linéaire général en grande dimension: application à des approches``multi-omiques''pour l'étude de la qualité des graines M Perrot-Dockès, C Lévy-Leduc, G Cueff, L Rajjou Intégration de données biologiques approches informatiques et statistiques, 2022 | | 2022 |
| Some detection tests for low complexity data models and unknown background distribution D Mary, S Bourguignon, E Roquain, S Sulis, M Perrot-Dockes arXiv preprint arXiv:2012.03534, 2020 | | 2020 |
| Méthodes régularisées pour l’analyse de données multivariées en grande dimension: théorie et applications. M Perrot-Dockès Université Paris-Saclay (ComUE), 2019 | | 2019 |
| Introduction to MultiVarSel M Perrot-Dockès, C Lévy-Leduc, J Chiquet | | 2019 |
| BlockCov M Perrot-Dockès, C Lévy-Leduc | | 2019 |
| Multivariate statistical modelling for QTL detection and marker selection in a bi-parental grapevine population C Brault, M Perrot-Dockès, A Doligez, J Chiquet, L Le Cunff, T Flutre 17. Meeting of the EUCARPIA Section Biometrics in Plant Breeding, np, 2018 | | 2018 |
| Quelques tests de détection s’ adaptanta la distribution du bruit de fond en astronomie D Mary, É Roquain, M Perrot-Dockes, S Sulis, S Bourguignon | | |
| Variable selection in multivariate linear models taking into account the dependence M Perrot-Dockès, C Lévy-Leduc, J Chiquet, L Sansonnet | | |
| Sélection de variables dans le modele linéaire multivarié en grande dimension avec prise en compte de la dépendance M Perrot-Dockes, LL Céline, J Chiquet, L Sansonnet | | |
