| 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, 2016 | 259 | 2016 |
| Unbalanced expression of CK2 kinase subunits is sufficient to drive epithelial-to-mesenchymal transition by Snail1 induction A Deshiere, E Duchemin-Pelletier, E Spreux, D Ciais, F Combes, ... Oncogene 32 (11), 1373, 2013 | 96 | 2013 |
| Identification of a novel BET bromodomain inhibitor‐sensitive, gene regulatory circuit that controls Rituximab response and tumour growth in aggressive lymphoid cancers A Emadali, S Rousseaux, J Bruder‐Costa, C Rome, S Duley, S Hamaidia, ... EMBO molecular medicine 5 (8), 1180-1195, 2013 | 88 | 2013 |
| An evaluation of custom microarray applications: the oligonucleotide design challenge S Lemoine, F Combes, S Le Crom Nucleic acids research 37 (6), 1726-1739, 2009 | 79 | 2009 |
| Goulphar: rapid access and expertise for standard two-color microarray normalization methods S Lemoine, F Combes, N Servant, S Le Crom BMC bioinformatics 7 (1), 467, 2006 | 75 | 2006 |
| Calibration plot for proteomics: A graphical tool to visually check the assumptions underlying FDR control in quantitative experiments Q Giai Gianetto, F Combes, C Ramus, C Bruley, Y Couté, T Burger Proteomics 16 (1), 29-32, 2016 | 71 | 2016 |
| Adipose gene expression prior to weight loss can differentiate and weakly predict dietary responders DM Mutch, MR Temanni, C Henegar, F Combes, V Pelloux, C Holst, ... PloS one 2 (12), e1344, 2007 | 54 | 2007 |
| Uranium perturbs signaling and iron uptake response in Arabidopsis thaliana roots F Doustaly, F Combes, JB Fiévet, S Berthet, V Hugouvieux, O Bastien, ... Metallomics 6 (4), 809-821, 2014 | 38 | 2014 |
| Proteomic characterization of human exhaled breath condensate M Lacombe, C Marie-Desvergne, F Combes, A Kraut, C Bruley, ... Journal of breath research 12 (2), 021001, 2018 | 37 | 2018 |
| Bioinformatics Tools and Workflow to Select Blood Biomarkers for Early Cancer Diagnosis: An Application to Pancreatic Cancer Y Vandenbrouck, D Christiany, F Combes, V Loux, V Brun PROTEOMICS, 1800489, 2019 | 27 | 2019 |
| Protein-Level Statistical Analysis of Quantitative Label-Free Proteomics Data with ProStaR S Wieczorek, F Combes, H Borges, T Burger Proteomics for Biomarker Discovery, 225-246, 2019 | 16 | 2019 |
| Designing an In Silico Strategy to Select Tissue-Leakage Biomarkers Using the Galaxy Framework L Nguyen, V Brun, F Combes, V Loux, Y Vandenbrouck Proteomics for Biomarker Discovery, 275-289, 2019 | 13 | 2019 |
| PEPA test: fast and powerful differential analysis from relative quantitative proteomics data using shared peptides L Jacob, F Combes, T Burger Biostatistics 20 (4), 632-647, 2018 | 6 | 2018 |
| Comprehensive and comparative exploration of the Atp7b−/− mouse plasma proteome M Lacombe, M Jaquinod, L Belmudes, Y Couté, C Ramus, F Combes, ... Metallomics, 2020 | 4 | 2020 |
| Package ‘cp4p’ QG Gianetto, F Combes, C Ramus, MQG Gianetto | 2 | 2019 |
| Extracting transcriptional regulatory modules from a large microarray compendium using a graph-based approach: application to the response of Arabidopsis thaliana under stress … F Boyer, F Combes, J Bourguignon, Y Vandenbrouck TIC Signal Process Proc Ser 48, 23-27, 2009 | 2 | 2009 |
| Design of oligonucleotide probes for microarrays: which software for which needs F Combes, S Lemoine, S Le Crom Posters proc. JOBIM, 2005 | 1 | 2005 |
| Package ‘DAPARdata’ S Wieczorek, F Combes | | 2016 |
| Calibration Plot for Proteomics (CP4P): A graphical tool to visually check the assumptions QG Gianetto, F Combes, C Ramus | | 2015 |
| Exploring the Response of Plants Grown under Uranium Stress F Doustaly, S Berthet, J Bourguignon, F Combes, Y Vandenbrouck, ... | | 2014 |
