| DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics S Wieczorek, F Combes, C Lazar, Q Giai Gianetto, L Gatto, A Dorffer, ... Bioinformatics 33 (1), 135-136, 2017 | 259 | 2017 |
| Mass-spectrometry-based spatial proteomics data analysis using pRoloc and pRolocdata L Gatto, LM Breckels, S Wieczorek, T Burger, KS Lilley Bioinformatics 30 (9), 1322-1324, 2014 | 104 | 2014 |
| A peptide-level multiple imputation strategy accounting for the different natures of missing values in proteomics data QG Gianetto, S Wieczorek, Y Couté, T Burger BioRxiv, 2020.05. 29.122770, 2020 | 24 | 2020 |
| Protein-level statistical analysis of quantitative label-free proteomics data with ProStaR S Wieczorek, F Combes, H Borges, T Burger Proteomics for Biomarker Discovery: Methods and Protocols, 225-246, 2019 | 16 | 2019 |
| Five simple yet essential steps to correctly estimate the rate of false differentially abundant proteins in mass spectrometry analyses S Wieczorek, QG Gianetto, T Burger Journal of proteomics 207, 103441, 2019 | 12 | 2019 |
| Guiding the search in the no region of the phase transition problem with a partial subsumption test S Wieczorek, G Bisson, MB Gordon Machine Learning: ECML 2006: 17th European Conference on Machine Learning …, 2006 | 7 | 2006 |
| Clustering of Molecules: Influence of the Similarity Measures S Aci, G Bisson, S Roy, S Wieczorek Selected Contributions in Data Analysis and Classification, 433-444, 2007 | 4 | 2007 |
| A new take on missing value imputation for bottom-up label-free LC-MS/MS proteomics L Etourneau, L Fancello, S Wieczorek, N Varoquaux, T Burger bioRxiv, 2023.11. 09.566355, 2023 | 2 | 2023 |
| Statistical analysis of quantitative peptidomics and peptide-level proteomics data with Prostar M Tardif, E Fremy, AM Hesse, T Burger, Y Couté, S Wieczorek Statistical Analysis of Proteomic Data: Methods and Tools, 163-196, 2021 | 2 | 2021 |
| DAPAR and ProStaR user manual S Wieczorek, F Combes, T Burger Bioconductor. https://www. bioconductor. org/packages/release/bioc/vignettes …, 2018 | 2 | 2018 |
| The signal: statistical aspects, normalisation, elementary analysis S Wieczorek Chemogenomics and Chemical Genetics: A User's Introduction for Biologists …, 2011 | 1 | 2011 |
| Criblages phénotypiques et «génétique chimique directe»: Une approche innovante pour la découverte de molécules bio-actives et/ou de candidats-médicaments E SANS-SOLEILHAC, C Barette, S Wieczorek, S Roy, E Maréchal, ... Spectra analyse 32 (233), 33-37, 2003 | 1 | 2003 |
| Guiding ilp search in the sparse solutions region with a partial subsumption test S Wieczorek, G Bisson, MB Gordon European Conference on Machine Learning 4212, 817-824, 0 | 1 | |
| Package ‘DAPARdata’ S Wieczorek, F Combes, MS Wieczorek | | 2016 |
| Package ‘MSnbase’ L Gatto, G Yu, S Wieczorek, VC Lazar, V Petyuk, T Naake, S Gibb, ... | | 2013 |
| Package ‘pRoloc’ L Gatto, T Burger, S Wieczorek, ML Gatto, I Biobase, LT Rcpp, ... | | 2013 |
| Prediction of subplastidial localization of chloroplast proteins from spectral count data-Comparison of machine learning algorithms T Burger, S Wieczorek, C Masselon, D Salvi, N Rolland, M Ferro RECOMB sat. conf. on proteomics 2012, 2012 | | 2012 |
| Clustering Libraries of Compounds into Families: Asymmetry-Based Similarity Measure to Categorize Small Molecules S Wieczorek, S Aci, G Bisson, MB Gordon, L Lafanechere, E Maréchal, ... Bioinformatics-Computational Biology and Modeling, 229-244, 2011 | | 2011 |
| Une mesure d'inclusion entre objets structurés. Application à la classification de molécules. S Wieczorek Université Joseph-Fourier-Grenoble I, 2009 | | 2009 |
| Criblages phenotypiques et<>. Une approche innovante pour la decouverte de molecules bio-actives et/ou de candidats-medicaments E Sans-Soleilhac, C Barette, S Wieczorek, S Roy, E Marechal, ... SPECTRA ANALYSE 32, 33-37, 2003 | | 2003 |
