Demo Data from EDBT 2026 / reviewers in the wild / expert
Yohann Couté
dblp:192/8262
· DBLP profile ↗
3ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0003-3896-6196ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
3 papers |
Bioinformatics and computational biology · 100% |
Topics — the 6 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
proteomics |
0.7 | 2 | 2020 | Proline: an efficient and user-friendly software suite for large-scale proteomics · Bioinform. 2020 DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics · Bioinform. 2017 |
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis |
0.6 | 2 | 2021 | Proline: an efficient and user-friendly software suite for large-scale proteomics · Bioinform. 2020 Well Plate Maker: a user-friendly randomized block design application to limit batch effects in large-scale biomedical studies · Bioinform. 2021 |
Bioinformatics and computational biology › omics data analysis
batch effect correction |
0.5 | 1 | 2021 | Well Plate Maker: a user-friendly randomized block design application to limit batch effects in large-scale biomedical studies · Bioinform. 2021 |
Bioinformatics and computational biology › computational microbiology › microbiome analysis
differential abundance testing |
0.3 | 1 | 2017 | DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics · Bioinform. 2017 |
Bioinformatics and computational biology › proteomics
quantitative proteomics |
0.3 | 1 | 2017 | DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics · Bioinform. 2017 |
Bioinformatics and computational biology › proteomics › quantitative proteomics
label-free quantification |
0.1 | 1 | 2020 | Proline: an efficient and user-friendly software suite for large-scale proteomics · Bioinform. 2020 |
Methods — techniques the papers use, named apart from their topics
randomization · 0.5graphical user interface · 0.5DDA label-free quantification · 0.4peptide intensity aggregation · 0.3null hypothesis significance testing · 0.3normalization · 0.3imputation · 0.3false discovery rate · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Well Plate Maker: a user-friendly randomized block design application to limit batch effects in large-scale biomedical studiesabstractSUMMARY: Many factors can influence results in clinical research, in particular bias in the distribution of samples prior to biochemical preparation. Well Plate Maker is a user-friendly application to design single- or multiple-well plate assays. It allows multiple group experiments to be randomized and therefore helps to reduce possible batch effects. Although primarily fathered to optimize the design of clinical sample analysis by high throughput mass spectrometry (e.g. proteomics or metabolomics), it includes multiple options to limit edge-of-plate effects, to incorporate control samples or to limit cross-contamination. It thus fits the constraints of many experimental fields. AVAILABILITY AND IMPLEMENTATION: Well Plate Maker is implemented in R and available at Bioconductor repository (https://bioconductor.org/packages/wpm) under the open source Artistic 2.0 license. In addition to classical scripting, it can be used through a graphical user interface, developed with Shiny technology. Hélène Borges, Anne-Marie Hesse, Alexandra Kraut, Yohann Couté, Virginie Brun, Thomas Burger |
Bioinform. | 4 |
| 2020 | Proline: an efficient and user-friendly software suite for large-scale proteomicsabstractMOTIVATION: The proteomics field requires the production and publication of reliable mass spectrometry-based identification and quantification results. Although many tools or algorithms exist, very few consider the importance of combining, in a unique software environment, efficient processing algorithms and a data management system to process and curate hundreds of datasets associated with a single proteomics study. RESULTS: Here, we present Proline, a robust software suite for analysis of MS-based proteomics data, which collects, processes and allows visualization and publication of proteomics datasets. We illustrate its ease of use for various steps in the validation and quantification workflow, its data curation capabilities and its computational efficiency. The DDA label-free quantification workflow efficiency was assessed by comparing results obtained with Proline to those obtained with a widely used software using a spiked-in sample. This assessment demonstrated Proline's ability to provide high quantification accuracy in a user-friendly interface for datasets of any size. AVAILABILITY AND IMPLEMENTATION: Proline is available for Windows and Linux under CECILL open-source license. It can be deployed in client-server mode or in standalone mode at http://proline.profiproteomics.fr/#downloads. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. David Bouyssié, Anne-Marie Hesse, Emmanuelle Mouton-Barbosa, Magali Rompais, Charlotte Macron, Christine Carapito, Anne Gonzalez de Peredo, Yohann Couté, Véronique Dupierris, Alexandre Burel, Jean-Philippe Menetrey, Andrea Kalaitzakis, Julie Poisat, Aymen Romdhani, Odile Burlet-Schiltz, Sarah Cianférani, Jerome Garin, Christophe Bruley |
Bioinform. | 8 |
| 2017 | DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomicsabstractDAPAR and ProStaR are software tools to perform the statistical analysis of label-free XIC-based quantitative discovery proteomics experiments. DAPAR contains procedures to filter, normalize, impute missing value, aggregate peptide intensities, perform null hypothesis significance tests and select the most likely differentially abundant proteins with a corresponding false discovery rate. ProStaR is a graphical user interface that allows friendly access to the DAPAR functionalities through a web browser. AVAILABILITY AND IMPLEMENTATION: DAPAR and ProStaR are implemented in the R language and are available on the website of the Bioconductor project (http://www.bioconductor.org/). A complete tutorial and a toy dataset are accompanying the packages. CONTACT: [email protected], [email protected], [email protected]. Samuel Wieczorek, Florence Combes, Cosmin Lazar, Quentin Giai Gianetto, Laurent Gatto, Alexia Dorffer, Anne-Marie Hesse, Yohann Couté, Myriam Ferro, Christophe Bruley, Thomas Burger |
Bioinform. | 8 |