EDBT 2026 Demo / reviewers in the wild / expert
Grégory Genta-Jouve
dblp:160/3381
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-9239-4371ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2
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
2 papers |
Bioinformatics and computational biology · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis |
0.4 | 1 | 2019 | MetWork: a web server for natural products anticipation · Bioinform. 2019 |
Bioinformatics and computational biology
metabolomics |
0.2 | 1 | 2015 | MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis · Bioinform. 2015 |
Bioinformatics and computational biology
multi-objective optimization |
0.2 | 1 | 2015 | MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis · Bioinform. 2015 |
Methods — techniques the papers use, named apart from their topics
molecular networking · 0.4MS/MS spectra prediction · 0.4multi-objective evolutionary optimization · 0.2closed-loop experimentation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | MetWork: a web server for natural products anticipationabstractMOTIVATION: The annotation of natural products and more generally small molecules is one of the major drawbacks in untargeted mass spectrometry analysis. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments. Despite the great potential of this tool, the annotation is usually performed manually by the expert as only few spectral libraries are available. RESULTS: Herein we propose a web server of in silico metabolization of metabolites that represents a full implementation of the metabolome consistency concept. The workflow is based on MS/MS data, organized in molecular network using the Global Natural Products Social Molecular Networking (GNPS) platform, a collaborative library of reactions and a MS/MS spectra prediction module. Having one node identified in the molecular network, the server generates putative structures and predict the associated MS/MS spectra when the exact mass is detected in the network. A similarity comparison between the MS/MS spectra is then performed in order to annotate the node. AVAILABILITY AND IMPLEMENTATION: The web server is available at: https://metwork.pharmacie.parisdescartes.fr. Yann Beauxis, Grégory Genta-Jouve |
Bioinform. | 2 |
| 2015 | MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysisabstractAbstract Summary: Developing liquid chromatography tandem mass spectrometry (LC-MS/MS) analyses of (bio)chemicals is both time consuming and challenging, largely because of the large number of LC and MS instrument parameters that need to be optimized. This bottleneck significantly impedes our ability to establish new (bio)analytical methods in fields such as pharmacology, metabolomics and pesticide research. We report the development of a multi-platform, user-friendly software tool MUSCLE (multi-platform unbiased optimization of spectrometry via closed-loop experimentation) for the robust and fully automated multi-objective optimization of targeted LC-MS/MS analysis. MUSCLE shortened the analysis times and increased the analytical sensitivities of targeted metabolite analysis, which was demonstrated on two different manufacturer’s LC-MS/MS instruments. Availability and implementation: Available at http://www.muscleproject.org. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. James Bradbury 0001, Grégory Genta-Jouve, James William Allwood, Warwick B. Dunn, Royston Goodacre, Joshua D. Knowles, Shan He 0001, Mark R. Viant |
Bioinform. | 2 |