| Gene regulatory network reconstruction using Bayesian networks, the Dantzig Selector, the Lasso and their meta-analysis M Vignes, J Vandel, D Allouche, N Ramadan-Alban, C Cierco-Ayrolles, ... PloS one 6 (12), e29165, 2011 | 116 | 2011 |
| The dynamics of root meristem distribution in the soil L Dupuy, M Vignes, BM McKenzie, PJ White Plant, cell & environment 33 (3), 358-369, 2010 | 41 | 2010 |
| Gene clustering via integrated Markov models combining individual and pairwise features M Vignes, F Forbes IEEE/ACM transactions on computational biology and bioinformatics 6 (2), 260-270, 2008 | 31 | 2008 |
| Bridging physiological and evolutionary time‐scales in a gene regulatory network G Marchand, VA Huynh‐Thu, NC Kane, S Arribat, D Varès, D Rengel, ... New Phytologist 203 (2), 685-696, 2014 | 16 | 2014 |
| A model-based approach to gene clustering with missing observation reconstruction in a Markov random field framework J Blanchet, M Vignes Journal of Computational Biology 16 (3), 475-486, 2009 | 13 | 2009 |
| Gene regulatory networks: a primer in biological processes and statistical modelling O Angelin-Bonnet, PJ Biggs, M Vignes Gene Regulatory Networks, 347-383, 2019 | 12 | 2019 |
| A panel of learning methods for the reconstruction of gene regulatory networks in a systems genetics context D Allouche, C Cierco-Ayrolles, S De Givry, G Guillermin, B Mangin, ... Gene Network Inference, 9-31, 2013 | 11 | 2013 |
| An algorithm for the simulation of the growth of root systems on deformable domains LX Dupuy, M Vignes Journal of theoretical biology 310, 164-174, 2012 | 11 | 2012 |
| Exact and approximate inference in graphical models: variable elimination and beyond N Peyrard, MJ Cros, S de Givry, A Franc, S Robin, R Sabbadin, T Schiex, ... arXiv preprint arXiv:1506.08544, 2015 | 9 | 2015 |
| Sparse regression and support recovery with L2-boosting algorithms M Champion, C Cierco-Ayrolles, S Gadat, M Vignes Journal of Statistical Planning and Inference 155, 19-41, 2014 | 9 | 2014 |
| Inferring networks from multiple samples with consensus lasso N Villa-Vialaneix, M Vignes, N Viguerie, MS Cristobal Quality Technology & Quantitative Management 11 (1), 39-60, 2014 | 9 | 2014 |
| Inferring large graphs using ℓ 1 -penalized likelihood M Champion, V Picheny, M Vignes Statistics and Computing 28 (4), 905-921, 2018 | 7 | 2018 |
| Combined expression data with missing values and gene interaction network analysis: a Markovian integrated approach J Blanchet, M Vignes 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering …, 2007 | 5 | 2007 |
| Extended Bayesian scores for reconstructing gene regulatory networks J Vandel, B Mangin, M Vignes, S de Givry ECCS-10 workshop on graphical models for reasoning on biological systems …, 2010 | 4 | 2010 |
| Integrated Markov models for clustering genes combining individual features and pairwise relationships M Vignes, F Forbes 4th workshop on Statistical methods for post-genomic data, Toulouse, France, 2006 | 4 | 2006 |
| Reconstruction quality of a biological network when its constituting elements are partially observed V Picheny, J Vandel, M Vignes, N Villa-Vialaneix Seventeenth International Conference on Artificial Intelligence and …, 2014 | 3 | 2014 |
| Meristematic waves, a new approach to root architecture dynamics L Dupuy, M Vignes, B McKenzie, PJ White Journees Ouvertes en Biologie Informatique Mathematiques, 97, 2009 | 3 | 2009 |
| Clustering with incomplete dependent data J Blanchet, F Forbes, M Vignes Actes des 39esJournées De Statistiques, Angers, 2007 | 3 | 2007 |
| Champs de Markov cachés et fusion de données individuelles et pairées pour l’identification de groupes de gènes F Forbes, M Vignes Actes des 6esJournées Ouvertes Biologie, Informatique et Mathématiques, Lyon, 2005 | 2 | 2005 |
| Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks A White, M Vignes Gene Regulatory Networks, 111-142, 2019 | 1 | 2019 |
Simon de GivryChercheur INRAE MIAT, HdRVerified email at inrae.fr
