Unraveling the effects of the gut microbiota composition and function on horse endurance physiology, (2019) Plancade S, Clark A, Philippe C, Helbling JC, Moisan MP, Esquerré D, Le Moyec L, Robert C, Barrey E, Mach N, , Sci Rep, 9(1):9620.
New
genetic biomarkers to differentiate non-pathogenic
from clinically
relevant Bacillus cereus strains, (2021), Kavanaugh
DW,
Glasset B, Dervyn R, Guérin C, Plancade
S, Herbin S, Brisabois A, Nicolas P, Ramarao N. ,
Clin Microbiol
Infect.
Benefits
of
Iterative Searches of Large Databases to Interpret
Large Human Gut
Metaproteomic Data Sets, (2021) Bassignani
A,
Plancade S,
Berland M, Blein-Nicolas M, Guillot A, Chevret D, Moritz
C, Huet S,
Rizkalla S, Clément K, Doré J, Langella O, Juste C,
J Proteome Res, 20(3):1522-1534.
Lactobacillus paracasei CNCM I-3689 reduces vancomycin-resistant Enterococcus persistence and promotes Bacteroidetes resilience in the gut following antibiotic challenge, (2018) R Crouzet, L., Derrien, M., Cherbuy, C., Plancade, S., Foulon,M., Chalin, B., van Hylckama Vlieg, J.E.T., Grompone, G., Rigottier-Gois, Serror, P., Scientific Reports, 8(1)
Inferring Aggregated Functional Traits from Metagenomic Data Using Constrained Non-Negative Matrix Factorization: Application to Fiber Degradation in the Human Gut Microbiota, (2016) Raguideau, S, Plancade, S, Pons, N., Leclerc, M. Laroche, B. PLOS Comput. Bio.
A new statistical method for curve group analysis of longitudinal geneexpression data illustrated for breast cancer in the NOWAC postgenome cohort as a proof of principle. Lund, E., Holden, L., Bøvelstad, H., Plancade, S., Mode, N., Günther, C.-C., Nuel, G., Thalabard, J.-C., Holden, M. (2016). BMC Medical Research Methodology, 16.
Integrated mRNA and miRNA expression profiling in blood reveals candidate biomarkers associated with endurance exercise in the horse, Mach, N., Plancade, S., Pacholewska, A., Lecardonnel, J., Rivière, J., Moroldo, M., Vaiman, A., Morgenthaler, C., Beinat, M., Névot, A., Robert, C., Barrey, E. (2016). Scientific Reports.
A generic methodological framework for studying single cell motility in high-throughput time-lapse data, Schoenauer Sebag A., Plancade S., Raulet-Tomkiewicz C., Barouki R., Vert J.P., Walter, T. (2015) BioInfo, i320-i328.
A processual model for functional analyses of carcinogenesis in the prospective cohort design, Lund E.*, Plancade S.*, Nuel G., Bovelstad H. and Thalabard J.C.
Adapative estimation of the conditional distribution function from current status data, Plancade, S. (2013), J. Statist. Plann. Inference, vol 143, p 1466-1485.
Generalization of the normal-exponential model: exploration of a more accurate parametrisation for the signal distribution on Illumina BeadArrays, Plancade, S., Rozenholc, Y., Lund, E. (2012), BMC Bioinfo, vol 13 (329)
Transcriptional output in a prospective design conditionally on follow-up and exposure -the multistage model of cancer, Lund, E. and Plancade, S. (2012), Int. J. Mol. Epidemiol. Genet., vol 3 (2), p 107-114
Guidelines for controlled trials of drugs in migraine: Third edition. A guide for inverstigators, Internation Headache Society Clinical Trials Subcommittee members: Tfelt-Hansen, P. et al (2011), Cephalgia, vol 32 (1), p 6-38.
Nonparametric estimation of hazard rate in presence of censoring, Plancade, S (2010), Metrika, vol 74, p 313-347.
Estimation of the density of regression errors by pointwise model selection, Plancade, S (2009), Math. Methods Statist., vol 18 (4), p 341-374.
Nonparametric estimation of the density of the regression noise, Plancade S (2008), C. R. Acad. Sci., vol 346 (7-8), p 461-466.